From a9d5ee4482a7138fa06b45de6bf04626e4c1f98b Mon Sep 17 00:00:00 2001 From: enrique Date: Wed, 27 Sep 2023 10:57:35 +0200 Subject: [PATCH 01/12] added new metric functions --- ...jective_vision_deep_learning_previous_v.py | 6 +- .../town_01_anticlockwise.launch | 2 +- .../town_01_clockwise.launch | 2 +- .../town_02_anticlockwise.launch | 6 +- ..._02_anticlockwise_single_ad_npc_low.launch | 71 +++++++++++++++++++ .../town_02_clockwise.launch | 2 +- .../default_carla_subjective_vision.yml | 5 +- behavior_metrics/utils/configuration.py | 2 + behavior_metrics/utils/controller_carla.py | 3 +- behavior_metrics/utils/metrics_carla.py | 51 ++++++++++++- 10 files changed, 139 insertions(+), 11 deletions(-) create mode 100644 behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch diff --git a/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py b/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py index 32211898..ca4a1fb8 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py +++ b/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py @@ -124,7 +124,7 @@ def execute(self): image_2 = self.camera_2.getImage().data image_3 = self.camera_3.getImage().data - cropped = image[230:-1,:] + cropped = image[200:-1,:] if self.cont < 20: self.cont += 1 @@ -195,6 +195,10 @@ def execute(self): self.motors.sendThrottle(throttle) self.motors.sendSteer(steer) self.motors.sendBrake(break_command) + + if vehicle_speed >= 35: + self.motors.sendThrottle(0.0) + self.motors.sendBrake(0.0) if self.previous_commanded_throttle != None: a = np.array((throttle, steer, break_command)) diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise.launch b/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise.launch index 061dd0db..47aba9f9 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise.launch +++ b/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise.launch @@ -56,7 +56,7 @@ - + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_clockwise.launch b/behavior_metrics/configs/CARLA_launch_files/town_01_clockwise.launch index 9a833b83..ea50d689 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_01_clockwise.launch +++ b/behavior_metrics/configs/CARLA_launch_files/town_01_clockwise.launch @@ -28,7 +28,7 @@ - + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise.launch b/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise.launch index 4fa3bebe..e56b89bb 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise.launch +++ b/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise.launch @@ -18,7 +18,7 @@ - + @@ -35,7 +35,7 @@ - + @@ -55,7 +55,7 @@ - + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch b/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch new file mode 100644 index 00000000..2a29d3ab --- /dev/null +++ b/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch @@ -0,0 +1,71 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_clockwise.launch b/behavior_metrics/configs/CARLA_launch_files/town_02_clockwise.launch index 5be79bf0..cc7c08d5 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_02_clockwise.launch +++ b/behavior_metrics/configs/CARLA_launch_files/town_02_clockwise.launch @@ -25,7 +25,7 @@ - + diff --git a/behavior_metrics/configs/default_carla_subjective_vision.yml b/behavior_metrics/configs/default_carla_subjective_vision.yml index 6215ddeb..77365d0d 100644 --- a/behavior_metrics/configs/default_carla_subjective_vision.yml +++ b/behavior_metrics/configs/default_carla_subjective_vision.yml @@ -37,7 +37,7 @@ Behaviors: PilotTimeCycle: 100 AsyncMode: False Parameters: - Model: '20230428-103315_pilotnet_model_3_151_cp.h5' + Model: '20230517-094715_pilotnet_model_3_15+101_cp.h5' ImageCropped: True ImageSize: [ 200,66 ] ImageNormalized: True @@ -47,8 +47,9 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_02_anticlockwise_low.launch + World: configs/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch RandomSpawnPoint: False + MultiCar: True Dataset: In: '/tmp/my_bag.bag' Out: '' diff --git a/behavior_metrics/utils/configuration.py b/behavior_metrics/utils/configuration.py index 5a4bbafc..f475e32f 100644 --- a/behavior_metrics/utils/configuration.py +++ b/behavior_metrics/utils/configuration.py @@ -140,6 +140,8 @@ def initialize_configuration(self, config_data): self.spawn_points = config_data['Behaviors']['Simulation']['SpawnPoints'] else: self.spawn_points = [] + if 'MultiCar' in config_data['Behaviors']['Simulation']: + self.multicar = config_data['Behaviors']['Simulation']['MultiCar'] if self.robot_type == 'f1rl': self.action_set = robot['Parameters']['action_set'] diff --git a/behavior_metrics/utils/controller_carla.py b/behavior_metrics/utils/controller_carla.py index 3693ae67..e6c1f4e4 100644 --- a/behavior_metrics/utils/controller_carla.py +++ b/behavior_metrics/utils/controller_carla.py @@ -286,6 +286,7 @@ def record_metrics(self, metrics_record_dir_path, world_counter=None, brain_coun self.experiment_metrics_bag_filename = self.metrics_record_dir_path + self.time_str + '/' + self.time_str + '.bag' topics = [ + '/carla/npc_vehicle_1/odometry', '/carla/ego_vehicle/odometry', '/carla/ego_vehicle/collision', '/carla/ego_vehicle/lane_invasion', @@ -347,7 +348,7 @@ def stop_recording_metrics(self): self.experiment_metrics['experiment_total_real_time'] = end_time - self.pilot.pilot_start_time experiment_metrics_filename = self.metrics_record_dir_path + self.time_str + '/' + self.time_str - self.experiment_metrics = metrics_carla.get_metrics(self.experiment_metrics, self.experiment_metrics_bag_filename, self.map_waypoints, experiment_metrics_filename) + self.experiment_metrics = metrics_carla.get_metrics(self.experiment_metrics, self.experiment_metrics_bag_filename, self.map_waypoints, experiment_metrics_filename, self.pilot.configuration) self.save_metrics(first_images, last_images) for key, value in self.experiment_metrics.items(): diff --git a/behavior_metrics/utils/metrics_carla.py b/behavior_metrics/utils/metrics_carla.py index 3fa2e086..c1154e93 100644 --- a/behavior_metrics/utils/metrics_carla.py +++ b/behavior_metrics/utils/metrics_carla.py @@ -46,7 +46,8 @@ def circuit_distance_completed(checkpoints, lap_point): return diameter -def get_metrics(experiment_metrics, experiment_metrics_bag_filename, map_waypoints, experiment_metrics_filename): +def get_metrics(experiment_metrics, experiment_metrics_bag_filename, map_waypoints, experiment_metrics_filename, config): + time_counter = 5 while not os.path.exists(experiment_metrics_bag_filename): time.sleep(1) @@ -71,6 +72,13 @@ def get_metrics(experiment_metrics, experiment_metrics_bag_filename, map_waypoin for index, row in dataframe_pose.iterrows(): checkpoints.append(row) + if config.multicar: + data_file = experiment_metrics_bag_filename.split('.bag')[0] + '/carla-npc_vehicle_1-odometry.csv' + dataframe_pose = pd.read_csv(data_file) + checkpoints_2 = [] + for index, row in dataframe_pose.iterrows(): + checkpoints_2.append(row) + data_file = experiment_metrics_bag_filename.split('.bag')[0] + '/clock.csv' dataframe_clock = pd.read_csv(data_file) clock_points = [] @@ -116,6 +124,8 @@ def get_metrics(experiment_metrics, experiment_metrics_bag_filename, map_waypoin experiment_metrics, collisions_checkpoints = get_collisions(experiment_metrics, collision_points, dataframe_pose) experiment_metrics, lane_invasion_checkpoints = get_lane_invasions(experiment_metrics, lane_invasion_points, dataframe_pose) experiment_metrics['experiment_total_simulated_time'] = seconds_end - seconds_start + if config.multicar: + experiment_metrics = get_distance_other_vehicle(experiment_metrics, checkpoints, checkpoints_2) if 'bird_eye_view_images' in experiment_metrics: experiment_metrics['bird_eye_view_images_per_second'] = experiment_metrics['bird_eye_view_images'] / experiment_metrics['experiment_total_simulated_time'] @@ -628,3 +638,42 @@ def get_all_experiments_aggregated_metrics_boxplot(result, experiments_starting_ plt.ylim(0, max_value+max_value*0.1) plt.savefig(experiments_starting_time_str + '/' + experiment_metric_and_title['metric'] + '_boxplot.png', bbox_inches='tight') plt.close() + +def get_distance_other_vehicle(experiment_metrics, checkpoints, checkpoints_2): + dangerous_distance = 0 + close_distance = 0 + medium_distance = 0 + great_distance = 0 + total_distance = 0 + + for i, (point, point_2) in enumerate(zip(checkpoints, checkpoints_2)): + current_checkpoint = np.array([point['pose.pose.position.x'], point['pose.pose.position.y']]) + current_checkpoint_2 = np.array([point_2['pose.pose.position.x'], point_2['pose.pose.position.y']]) + + if i != 0: + distance_front = np.linalg.norm(current_checkpoint - current_checkpoint_2) + distance = np.linalg.norm(previous_point - current_checkpoint) + + # Analyzing + if 20 < distance_front < 50: + great_distance += distance + total_distance += distance + elif 15 < distance_front <= 20: + medium_distance += distance + total_distance += distance + elif 6 < distance_front <= 15: + close_distance += distance + total_distance += distance + elif distance_front <= 6: + dangerous_distance += distance + total_distance += distance + + previous_point = current_checkpoint + + experiment_metrics['dangerous_distance_km'] = dangerous_distance + experiment_metrics['close_distance_km'] = close_distance + experiment_metrics['medium_distance_km'] = medium_distance + experiment_metrics['great_distance_km'] = great_distance + experiment_metrics['total_distance_to_front_car'] = total_distance + + return experiment_metrics \ No newline at end of file From 08b935efcece1fd583896efe179b71ec81b4002e Mon Sep 17 00:00:00 2001 From: enrique Date: Wed, 27 Sep 2023 17:40:28 +0200 Subject: [PATCH 02/12] up to date --- .gitignore | 1 + LICENSE | 674 ++++++++++++++++++ README.md | 54 +- .../Carla/Maps/.gitignore | 0 .../brains/CARLA/brain_carla_slow_and_turn.py | 4 +- ...jective_vision_deep_learning_previous_v.py | 2 +- ...rain_carla_bird_eye_deep_learning_torch.py | 37 +- ..._bird_eye_deep_learning_torch_optimized.py | 162 +++++ ..._eye_deep_learning_torch_tensorrt_float.py | 165 +++++ ..._eye_deep_learning_torch_tensorrt_int_8.py | 170 +++++ .../pytorch/utils}/__init__.py | 0 .../pytorch/utils}/convlstm.py | 0 .../utils}/deepest_lstm_tinypilotnet.py | 0 .../pytorch/utils}/pilotnet.py | 0 .../pytorch/utils}/pilotnetStacked.py | 0 .../brain_carla_bird_eye_deep_learning.py | 36 +- ...in_carla_bird_eye_deep_learning_70_km_h.py | 191 +++++ ...n_carla_bird_eye_deep_learning_V_MAX_30.py | 2 +- ...rla_bird_eye_deep_learning_broken_input.py | 195 +++++ ...a_bird_eye_deep_learning_broken_input_2.py | 195 +++++ ...carla_bird_eye_deep_learning_previous_v.py | 2 +- ...rd_eye_deep_learning_previous_v_70_km_h.py | 197 +++++ ...e_deep_learning_previous_v_broken_input.py | 201 ++++++ ...deep_learning_previous_v_broken_input_2.py | 201 ++++++ ..._carla_bird_eye_deep_learning_tensor_rt.py | 10 +- ...in_carla_bird_eye_deep_learning_tf_lite.py | 24 +- ...e_deep_learning_x3_previous_v_t_t-4_t-9.py | 2 +- ...earning_x3_previous_v_t_t-4_t-9_70_km_h.py | 299 ++++++++ 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behavior_metrics/pilot_carla.py | 3 + behavior_metrics/profiles/default.yml | 2 +- behavior_metrics/robot/configurations/f1.yml | 2 +- .../robot/configurations/f1_laser.yml | 2 +- .../robot/configurations/turtlebot_laser.yml | 2 +- .../robot/interfaces/birdeyeview.py | 10 +- behavior_metrics/ui/tui/main_view.py | 2 +- behavior_metrics/utils/configuration.py | 19 +- behavior_metrics/utils/controller_carla.py | 5 +- behavior_metrics/utils/metrics_carla.py | 4 +- behavior_metrics/utils/traffic.py | 201 ++++++ requirements.txt | 6 +- 257 files changed, 5079 insertions(+), 1407 deletions(-) create mode 100644 LICENSE rename behavior_metrics/{birdview_v2_cache => birdview_v3_cache}/Carla/Maps/.gitignore (100%) rename behavior_metrics/brains/CARLA/{ => pytorch}/brain_carla_bird_eye_deep_learning_torch.py (84%) create mode 100644 behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_optimized.py create mode 100644 behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_tensorrt_float.py create mode 100644 behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_tensorrt_int_8.py rename behavior_metrics/brains/{agents => CARLA/pytorch/utils}/__init__.py (100%) rename behavior_metrics/brains/{f1/torch_utils => CARLA/pytorch/utils}/convlstm.py (100%) rename behavior_metrics/brains/{f1/torch_utils => CARLA/pytorch/utils}/deepest_lstm_tinypilotnet.py (100%) rename behavior_metrics/brains/{f1/torch_utils => CARLA/pytorch/utils}/pilotnet.py (100%) rename behavior_metrics/brains/{f1/torch_utils => CARLA/pytorch/utils}/pilotnetStacked.py (100%) rename behavior_metrics/brains/CARLA/{ => tensorflow}/brain_carla_bird_eye_deep_learning.py (88%) create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_70_km_h.py rename behavior_metrics/brains/CARLA/{ => tensorflow}/brain_carla_bird_eye_deep_learning_V_MAX_30.py (98%) create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input.py create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input_2.py rename behavior_metrics/brains/CARLA/{ => tensorflow}/brain_carla_bird_eye_deep_learning_previous_v.py (98%) create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_70_km_h.py create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input.py create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input_2.py rename behavior_metrics/brains/CARLA/{ => tensorflow}/brain_carla_bird_eye_deep_learning_tensor_rt.py (95%) rename behavior_metrics/brains/CARLA/{ => tensorflow}/brain_carla_bird_eye_deep_learning_tf_lite.py (88%) rename behavior_metrics/brains/CARLA/{ => tensorflow}/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py (99%) create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_70_km_h.py create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input.py create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input_2.py rename behavior_metrics/brains/CARLA/{ => tensorflow}/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py (98%) create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_70_km_h.py rename behavior_metrics/brains/CARLA/{ => tensorflow}/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_V_MAX_30.py (98%) create mode 100644 behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_broken_input.py create mode 100644 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(96%) rename behavior_metrics/configs/{ => gazebo}/default-drone.yml (100%) rename behavior_metrics/configs/{ => gazebo}/default-multiple.yml (93%) rename behavior_metrics/configs/{ => gazebo}/default-rl-dqn.yml (95%) rename behavior_metrics/configs/{ => gazebo}/default-rl-qlearn.yml (94%) rename behavior_metrics/configs/{ => gazebo}/default-rl.yml (100%) rename behavior_metrics/configs/{ => gazebo}/default.yml (95%) rename behavior_metrics/configs/{ => gazebo}/torch-multiple.yml (90%) delete mode 100644 behavior_metrics/models/carla_tf_models/20221214-102705_deepestLSTMTinyPilotNet_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_both_directions_all_towns_PAPER_cp.h5 delete mode 100644 behavior_metrics/models/carla_tf_models/20230126-183457_deepestLSTMTinyPilotNet_CARLA_14_12_dataset_bird_eye_400_epochs_no_flip_3_output_both_directions_all_towns__less_learning_rate_PAPER_cp.h5 rename behavior_metrics/models/{ => gazebo}/rl_models/actions_set_20221128_0938 (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/fingerprint.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/keras_metadata.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/saved_model.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.data-00000-of-00001 (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.index (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/fingerprint.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/keras_metadata.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/saved_model.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.data-00000-of-00001 (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.index (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/fingerprint.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/keras_metadata.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/saved_model.pb (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.data-00000-of-00001 (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.index (100%) rename behavior_metrics/models/{ => gazebo}/rl_models/qlearn/20230216-170351_Circuit-simple_States-sp1_Actions-simple_Rewards-followline_center_epsilon-0.05_epoch-4751_step-15001_reward-139266-qtable.npy (100%) create mode 100644 behavior_metrics/models/gazebo/tf_models/tf_models.txt rename behavior_metrics/models/{ => gazebo}/torch_models/model_lstm_pilotnet_torch.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_extreme.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_fullimg_extreme.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_h2.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_h2_extreme.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_h3_extreme.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_h4.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_h4_extreme.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_h5_extreme.ckpt (100%) rename behavior_metrics/models/{ => gazebo}/torch_models/model_pilotnet_torch_nocrop.ckpt (100%) create mode 100644 behavior_metrics/utils/traffic.py diff --git a/.gitignore b/.gitignore index 8d135fda..27c4827a 100644 --- a/.gitignore +++ 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If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Copyright (C) + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/README.md b/README.md index 0dc88a69..7f8ee756 100644 --- a/README.md +++ b/README.md @@ -3,17 +3,57 @@ [![Publish cuda 11 Docker image](https://github.com/JdeRobot/BehaviorMetrics/actions/workflows/generate_docker_cuda_11.yml/badge.svg)](https://github.com/JdeRobot/BehaviorMetrics/actions/workflows/generate_docker_cuda_11.yml) # Behavior Metrics -This project presents different approaches to the follow-the-line exercise but using artificial intelligence to complete the circuits. The solutions presented are: -- Using classification networks. -- Using regression networks. -- Using reinforcement learning. -- Solution for real robots. +This software tool provides evaluation capabilities for autonomous driving solutions using simulation. +We provide a series of quantitative metrics for the evaluation of autonomous driving solutions with support for two simulators, [CARLA](https://carla.org/) (main supported simulator) and [gazebo](https://gazebosim.org/home) (partial support). +Currently supported tasks include: -For more information about the project you can consult the [website of Behavior Metrics](https://jderobot.github.io/BehaviorMetrics/). +* Follow-lane +* Driving in traffic +* Navigation + +Each task comes with its own custom evaluation metrics that can help compare autonomous driving solutions. +The main component of the ego vehicle is the brain, which receives sensor data, manipulates it, and generates robot control commands based on it. +The inner part of the brain can be controlled by an end-to-end model, written in Tensorflow or PyTorch, a reinforcement learning policy, or even an explicitly programmed policy. + +The software provides two main pipelines, a graphical user interface (GUI) and a headless mode (scripted). +The first one is intended for testing one brain+model at a time and debugging it visually while the headless mode is intended for running lots of experiments at the same time for comparison of a batch of brain+models in different scenarios. + +architecture + +### Installation + +For more information about the project and how to install it, you can consult the [website of Behavior Metrics](https://jderobot.github.io/BehaviorMetrics/). + +### Examples + +We provide examples for the follow-lane task using CARLA: + +* For an example of a robot brain using a Tensorflow model for control with GUI pipeline, run: + +``` +python3 driver_carla.py -c configs/CARLA/default_carla_tensorflow.yml -g +``` + +* For an example of a robot brain using a PyTorch model for control with GUI pipeline, run: + +``` +python3 driver_carla.py -c configs/CARLA/default_carla_torch.yml -g +``` + +* For an example of an explicitly programmed robot brain with GUI pipeline, run: + +``` +python3 driver_carla.py -c configs/CARLA/default_carla.yml -g +``` + +* For an example of the headless pipeline, run: + +``` +python3 driver_carla.py -c configs/CARLA/default_carla_multiple.yml -s +``` ### Contributing to the project If you want to contribute, please first check out [CONTRIBUTING.md](CONTRIBUTING.md) section. config -architecture \ No newline at end of file diff --git a/behavior_metrics/birdview_v2_cache/Carla/Maps/.gitignore b/behavior_metrics/birdview_v3_cache/Carla/Maps/.gitignore similarity index 100% rename from behavior_metrics/birdview_v2_cache/Carla/Maps/.gitignore rename to behavior_metrics/birdview_v3_cache/Carla/Maps/.gitignore diff --git a/behavior_metrics/brains/CARLA/brain_carla_slow_and_turn.py b/behavior_metrics/brains/CARLA/brain_carla_slow_and_turn.py index 102dd05c..4b4f04c2 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_slow_and_turn.py +++ b/behavior_metrics/brains/CARLA/brain_carla_slow_and_turn.py @@ -65,7 +65,9 @@ def execute(self): image_2 = self.camera_2.getImage().data image_3 = self.camera_3.getImage().data - self.motors.sendThrottle(1) + self.motors.sendThrottle(0.5) + self.motors.sendSteer(0.05) + self.update_frame('frame_0', image) self.update_frame('frame_1', image_1) self.update_frame('frame_2', image_2) diff --git a/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py b/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py index ca4a1fb8..d9d46ec1 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py +++ b/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py @@ -16,7 +16,7 @@ from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_torch.py b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch.py similarity index 84% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_torch.py rename to behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch.py index 13373d43..1c86fb03 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_torch.py +++ b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch.py @@ -1,8 +1,11 @@ -from torchvision import transforms from PIL import Image -from brains.f1.torch_utils.pilotnet import PilotNet +from brains.CARLA.pytorch.utils.pilotnet import PilotNet from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH from os import path +from albumentations import ( + Compose, Normalize +) +from albumentations.pytorch.transforms import ToTensorV2 import numpy as np @@ -14,7 +17,7 @@ import math import carla -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' FLOAT = torch.FloatTensor class Brain: @@ -43,8 +46,9 @@ def __init__(self, sensors, actuators, model=None, handler=None, config=None): self.gpu_inference = config['GPU'] self.device = torch.device('cuda' if (torch.cuda.is_available() and self.gpu_inference) else 'cpu') self.first_image = None - self.transformations = transforms.Compose([ - transforms.ToTensor() + self.transformations = Compose([ + Normalize(), + ToTensorV2() ]) self.suddenness_distance = [] @@ -119,10 +123,10 @@ def execute(self): self.update_frame('frame_0', bird_eye_view_1) try: - #img = cv2.resize(bird_eye_view_1, (int(200), int(66))) img = cv2.resize(bird_eye_view_1, (int(66), int(200))) - img = Image.fromarray(img) - image = self.transformations(img).unsqueeze(0) + image = self.transformations(image=img) + image = image['image'] + image = image.unsqueeze(0) image = FLOAT(image).to(self.device) start_time = time.time() @@ -137,14 +141,19 @@ def execute(self): speed = self.vehicle.get_velocity() vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) - if vehicle_speed < 5: - self.motors.sendThrottle(1.0) - self.motors.sendSteer(0.0) - self.motors.sendBrake(0) - else: - self.motors.sendThrottle(throttle) + if vehicle_speed > 30: + self.motors.sendThrottle(0) self.motors.sendSteer(steer) self.motors.sendBrake(break_command) + else: + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) except Exception as err: print(err) diff --git a/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_optimized.py b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_optimized.py new file mode 100644 index 00000000..a7b6393d --- /dev/null +++ b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_optimized.py @@ -0,0 +1,162 @@ +from PIL import Image +from brains.CARLA.pytorch.utils.pilotnet import PilotNet +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from os import path +from albumentations import ( + Compose, Normalize +) +from albumentations.pytorch.transforms import ToTensorV2 + +import numpy as np + +import torch +import torchvision +import cv2 +import time +import os +import math +import carla + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' +FLOAT = torch.FloatTensor + +class Brain: + """Specific brain for the CARLA robot. See header.""" + + def __init__(self, sensors, actuators, model=None, handler=None, config=None): + """Constructor of the class. + + Arguments: + sensors {robot.sensors.Sensors} -- Sensors instance of the robot + actuators {robot.actuators.Actuators} -- Actuators instance of the robot + + Keyword Arguments: + handler {brains.brain_handler.Brains} -- Handler of the current brain. Communication with the controller + (default: {None}) + """ + self.motors = actuators.get_motor('motors_0') + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + self.handler = handler + self.cont = 0 + self.inference_times = [] + self.gpu_inference = config['GPU'] + self.device = torch.device('cuda' if (torch.cuda.is_available() and self.gpu_inference) else 'cpu') + self.first_image = None + self.transformations = Compose([ + Normalize(), + ToTensorV2() + ]) + + self.suddenness_distance = [] + self.previous_v = None + self.previous_w = None + + if config: + if 'ImageCrop' in config.keys(): + self.cropImage = config['ImageCrop'] + else: + self.cropImage = True + + if model: + if not path.exists(PRETRAINED_MODELS + model): + print("File " + model + " cannot be found in " + PRETRAINED_MODELS) + + #if config['UseOptimized']: + self.net = torch.jit.load(PRETRAINED_MODELS + model).to(self.device) +# self.clean_model() + #else: + # self.net = PilotNet((200,66,3), 3).to(self.device) + # self.net.load_state_dict(torch.load(PRETRAINED_MODELS + model,map_location=self.device)) + # self.net.eval() + else: + print("Brain not loaded") + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def execute(self): + """Main loop of the brain. This will be called iteratively each TIME_CYCLE (see pilot.py)""" + + self.cont += 1 + + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + try: + img = cv2.resize(bird_eye_view_1, (int(66), int(200))) + image = self.transformations(image=img) + image = image['image'] + image = image.unsqueeze(0) + image = FLOAT(image).to(self.device) + + start_time = time.time() + with torch.no_grad(): + prediction = self.net(image).cpu().numpy() if self.gpu_inference else self.net(image).numpy() + self.inference_times.append(time.time() - start_time) + + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed > 30: + self.motors.sendThrottle(0) + self.motors.sendSteer(steer) + self.motors.sendBrake(1.0) + else: + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except Exception as err: + print(err) + + diff --git a/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_tensorrt_float.py b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_tensorrt_float.py new file mode 100644 index 00000000..1be9db8c --- /dev/null +++ b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_tensorrt_float.py @@ -0,0 +1,165 @@ +from PIL import Image +from brains.CARLA.pytorch.utils.pilotnet import PilotNet +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from os import path +from albumentations import ( + Compose, Normalize +) +from albumentations.pytorch.transforms import ToTensorV2 + +import numpy as np + +import torch +import torchvision +import cv2 +import time +import os +import math +import carla + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' +FLOAT = torch.FloatTensor + +class Brain: + """Specific brain for the CARLA robot. See header.""" + + def __init__(self, sensors, actuators, model=None, handler=None, config=None): + """Constructor of the class. + + Arguments: + sensors {robot.sensors.Sensors} -- Sensors instance of the robot + actuators {robot.actuators.Actuators} -- Actuators instance of the robot + + Keyword Arguments: + handler {brains.brain_handler.Brains} -- Handler of the current brain. Communication with the controller + (default: {None}) + """ + self.motors = actuators.get_motor('motors_0') + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + self.handler = handler + self.cont = 0 + self.inference_times = [] + self.gpu_inference = config['GPU'] + self.device = torch.device('cuda' if (torch.cuda.is_available() and self.gpu_inference) else 'cpu') + self.first_image = None + self.transformations = Compose([ + Normalize(), + ToTensorV2() + ]) + + self.suddenness_distance = [] + self.previous_v = None + self.previous_w = None + + if config: + if 'ImageCrop' in config.keys(): + self.cropImage = config['ImageCrop'] + else: + self.cropImage = True + + if model: + if not path.exists(PRETRAINED_MODELS + model): + print("File " + model + " cannot be found in " + PRETRAINED_MODELS) + + if config['UseOptimized']: + print('Loading optimized model...') + print(PRETRAINED_MODELS + model) + + # Float y half TensorRT + self.net = torch.jit.load(PRETRAINED_MODELS + model).eval().to(self.device) +# self.clean_model() + else: + self.net = PilotNet((200,66,3), 3).to(self.device) + self.net.load_state_dict(torch.load(PRETRAINED_MODELS + model,map_location=self.device)) + else: + print("Brain not loaded") + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def execute(self): + """Main loop of the brain. This will be called iteratively each TIME_CYCLE (see pilot.py)""" + + self.cont += 1 + + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + try: + img = cv2.resize(bird_eye_view_1, (int(66), int(200))) + image = self.transformations(image=img) + image = image['image'] + image = image.unsqueeze(0) + image = FLOAT(image).to(self.device) + + start_time = time.time() + with torch.no_grad(): + prediction = self.net(image).cpu().numpy() if self.gpu_inference else self.net(image).numpy() + self.inference_times.append(time.time() - start_time) + + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed > 30: + self.motors.sendThrottle(0) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + else: + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except Exception as err: + print(err) + + diff --git a/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_tensorrt_int_8.py b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_tensorrt_int_8.py new file mode 100644 index 00000000..d7d05a2d --- /dev/null +++ b/behavior_metrics/brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch_tensorrt_int_8.py @@ -0,0 +1,170 @@ +from PIL import Image +from brains.CARLA.pytorch.utils.pilotnet import PilotNet +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from os import path +from albumentations import ( + Compose, Normalize +) +from albumentations.pytorch.transforms import ToTensorV2 + +import numpy as np + +import torch +import torchvision +import cv2 +import time +import os +import math +import carla + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' +FLOAT = torch.FloatTensor + +class Brain: + """Specific brain for the CARLA robot. See header.""" + + def __init__(self, sensors, actuators, model=None, handler=None, config=None): + """Constructor of the class. + + Arguments: + sensors {robot.sensors.Sensors} -- Sensors instance of the robot + actuators {robot.actuators.Actuators} -- Actuators instance of the robot + + Keyword Arguments: + handler {brains.brain_handler.Brains} -- Handler of the current brain. Communication with the controller + (default: {None}) + """ + self.motors = actuators.get_motor('motors_0') + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + self.handler = handler + self.cont = 0 + self.inference_times = [] + self.gpu_inference = config['GPU'] + self.device = torch.device('cuda') + self.first_image = None + self.transformations = Compose([ + Normalize(), + ToTensorV2() + ]) + + self.suddenness_distance = [] + self.previous_v = None + self.previous_w = None + + if config: + if 'ImageCrop' in config.keys(): + self.cropImage = config['ImageCrop'] + else: + self.cropImage = True + + if model: + if not path.exists(PRETRAINED_MODELS + model): + print("File " + model + " cannot be found in " + PRETRAINED_MODELS) + + if config['UseOptimized']: + print('Loading optimized model TensorRT INT8...') + print(PRETRAINED_MODELS + model) + + # INT 8 TensorRT + import torch_tensorrt + self.net = torch.jit.load(PRETRAINED_MODELS + model).eval().to(self.device) + compile_spec = {"inputs": [torch_tensorrt.Input([1, 3, 200, 66])], + "enabled_precisions": torch.int8, + } + self.net = torch_tensorrt.compile(self.net, **compile_spec).to(self.device) + else: + self.net = PilotNet((200,66,3), 3).to(self.device) + self.net.load_state_dict(torch.load(PRETRAINED_MODELS + model,map_location=self.device)) + else: + print("Brain not loaded") + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def execute(self): + """Main loop of the brain. This will be called iteratively each TIME_CYCLE (see pilot.py)""" + + self.cont += 1 + + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + try: + img = cv2.resize(bird_eye_view_1, (int(66), int(200))) + image = self.transformations(image=img) + image = image['image'] + image = image.unsqueeze(0) + image = FLOAT(image).to(self.device) + + start_time = time.time() + with torch.no_grad(): + prediction = self.net(image).cpu().numpy() if self.gpu_inference else self.net(image).numpy() + + self.inference_times.append(time.time() - start_time) + + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed > 30: + self.motors.sendThrottle(0) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + else: + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except Exception as err: + print(err) + + diff --git a/behavior_metrics/brains/agents/__init__.py b/behavior_metrics/brains/CARLA/pytorch/utils/__init__.py similarity index 100% rename from behavior_metrics/brains/agents/__init__.py rename to behavior_metrics/brains/CARLA/pytorch/utils/__init__.py diff --git a/behavior_metrics/brains/f1/torch_utils/convlstm.py b/behavior_metrics/brains/CARLA/pytorch/utils/convlstm.py similarity index 100% rename from behavior_metrics/brains/f1/torch_utils/convlstm.py rename to behavior_metrics/brains/CARLA/pytorch/utils/convlstm.py diff --git a/behavior_metrics/brains/f1/torch_utils/deepest_lstm_tinypilotnet.py b/behavior_metrics/brains/CARLA/pytorch/utils/deepest_lstm_tinypilotnet.py similarity index 100% rename from behavior_metrics/brains/f1/torch_utils/deepest_lstm_tinypilotnet.py rename to behavior_metrics/brains/CARLA/pytorch/utils/deepest_lstm_tinypilotnet.py diff --git a/behavior_metrics/brains/f1/torch_utils/pilotnet.py b/behavior_metrics/brains/CARLA/pytorch/utils/pilotnet.py similarity index 100% rename from behavior_metrics/brains/f1/torch_utils/pilotnet.py rename to behavior_metrics/brains/CARLA/pytorch/utils/pilotnet.py diff --git a/behavior_metrics/brains/f1/torch_utils/pilotnetStacked.py b/behavior_metrics/brains/CARLA/pytorch/utils/pilotnetStacked.py similarity index 100% rename from behavior_metrics/brains/f1/torch_utils/pilotnetStacked.py rename to behavior_metrics/brains/CARLA/pytorch/utils/pilotnetStacked.py diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py similarity index 88% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning.py rename to behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py index 19fbedfd..c58be794 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning.py +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py @@ -9,24 +9,25 @@ import carla from os import path from albumentations import ( - Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout ) from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError import tensorflow as tf -import os -os.environ['CUDA_VISIBLE_DEVICES'] = '-1' -#gpus = tf.config.experimental.list_physical_devices('GPU') -#for gpu in gpus: -# tf.config.experimental.set_memory_growth(gpu, True) +#import os +#os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +gpus = tf.config.experimental.list_physical_devices('GPU') +for gpu in gpus: + tf.config.experimental.set_memory_growth(gpu, True) class Brain: @@ -134,7 +135,8 @@ def execute(self): self.update_pose(self.pose.getPose3d()) - image_shape=(50, 150) + image_shape=(66, 200) + #image_shape=(50, 150) img_base = cv2.resize(bird_eye_view_1, image_shape) AUGMENTATIONS_TEST = Compose([ @@ -159,21 +161,15 @@ def execute(self): speed = self.vehicle.get_velocity() vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) - self.previous_speed = vehicle_speed - if vehicle_speed > 30: - self.motors.sendThrottle(0) + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) self.motors.sendSteer(steer) self.motors.sendBrake(break_command) - else: - if vehicle_speed < 5: - self.motors.sendThrottle(1.0) - self.motors.sendSteer(0.0) - self.motors.sendBrake(0) - else: - self.motors.sendThrottle(throttle) - self.motors.sendSteer(steer) - self.motors.sendBrake(break_command) except NotFoundError as ex: logger.info('Error inside brain: NotFoundError!') logger.warning(type(ex).__name__) diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_70_km_h.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_70_km_h.py new file mode 100644 index 00000000..80e75693 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_70_km_h.py @@ -0,0 +1,191 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + + +#import os +#os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +gpus = tf.config.experimental.list_physical_devices('GPU') +for gpu in gpus: + tf.config.experimental.set_memory_growth(gpu, True) + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model, compile=False) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + self.first_acceleration = True + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + img = np.expand_dims(img, axis=0) + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed < 70 and self.first_acceleration: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.first_acceleration = False + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_V_MAX_30.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_V_MAX_30.py similarity index 98% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_V_MAX_30.py rename to behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_V_MAX_30.py index 63b816d9..bda34764 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_V_MAX_30.py +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_V_MAX_30.py @@ -15,7 +15,7 @@ from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input.py new file mode 100644 index 00000000..37fcd41e --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input.py @@ -0,0 +1,195 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout, ChannelDropout +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + + +#import os +#os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +gpus = tf.config.experimental.list_physical_devices('GPU') +for gpu in gpus: + tf.config.experimental.set_memory_growth(gpu, True) + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model, compile=False) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + AUGMENTATIONS_TEST = Compose([ + GridDropout(p=1.0, ratio=0.9) + ]) + + bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1) + bird_eye_view_1 = bird_eye_view_1["image"] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + img = np.expand_dims(img, axis=0) + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input_2.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input_2.py new file mode 100644 index 00000000..37fcd41e --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_broken_input_2.py @@ -0,0 +1,195 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout, ChannelDropout +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + + +#import os +#os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +gpus = tf.config.experimental.list_physical_devices('GPU') +for gpu in gpus: + tf.config.experimental.set_memory_growth(gpu, True) + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model, compile=False) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + AUGMENTATIONS_TEST = Compose([ + GridDropout(p=1.0, ratio=0.9) + ]) + + bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1) + bird_eye_view_1 = bird_eye_view_1["image"] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + img = np.expand_dims(img, axis=0) + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_previous_v.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v.py similarity index 98% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_previous_v.py rename to behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v.py index 2c598e8c..9ab3105a 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_previous_v.py +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v.py @@ -15,7 +15,7 @@ from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_70_km_h.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_70_km_h.py new file mode 100644 index 00000000..62952e24 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_70_km_h.py @@ -0,0 +1,197 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_speed = 0 + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + self.first_acceleration = True + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + velocity_dim = np.full((150, 50), self.previous_speed/30) + new_img_vel = np.dstack((img, velocity_dim)) + img = new_img_vel + + img = np.expand_dims(img, axis=0) + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + + if vehicle_speed < 70 and self.first_acceleration: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.first_acceleration = False + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input.py new file mode 100644 index 00000000..2ac2ae31 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input.py @@ -0,0 +1,201 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_speed = 0 + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + AUGMENTATIONS_TEST = Compose([ + GridDropout(p=1.0, ratio=0.9) + ]) + + bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1) + bird_eye_view_1 = bird_eye_view_1["image"] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + velocity_dim = np.full((150, 50), self.previous_speed/30) + new_img_vel = np.dstack((img, velocity_dim)) + img = new_img_vel + + img = np.expand_dims(img, axis=0) + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input_2.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input_2.py new file mode 100644 index 00000000..2ac2ae31 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_previous_v_broken_input_2.py @@ -0,0 +1,201 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_speed = 0 + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + AUGMENTATIONS_TEST = Compose([ + GridDropout(p=1.0, ratio=0.9) + ]) + + bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1) + bird_eye_view_1 = bird_eye_view_1["image"] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + velocity_dim = np.full((150, 50), self.previous_speed/30) + new_img_vel = np.dstack((img, velocity_dim)) + img = new_img_vel + + img = np.expand_dims(img, axis=0) + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_tensor_rt.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tensor_rt.py similarity index 95% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_tensor_rt.py rename to behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tensor_rt.py index a597449c..08c170dc 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_tensor_rt.py +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tensor_rt.py @@ -15,10 +15,12 @@ from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError +from tensorflow.python.saved_model import signature_constants +from tensorflow.python.saved_model import tag_constants import tensorflow as tf #import os @@ -64,8 +66,8 @@ def __init__(self, sensors, actuators, handler, model, config=None): logger.info("** Load TF model **") logger.info("Using TensorRT models.....") - self.net = tf.saved_model.load(PRETRAINED_MODELS + model) - self.infer = self.net.signatures['serving_default'] + self.net = tf.saved_model.load(PRETRAINED_MODELS + model, tags=[tag_constants.SERVING]) + self.infer = self.net.signatures[signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY] self.output_tensorname = list(self.infer.structured_outputs.keys())[0] self.inf_func = self.tftrt_inference @@ -150,7 +152,7 @@ def execute(self): self.update_pose(self.pose.getPose3d()) - image_shape=(50, 150) + image_shape=(66, 200) img_base = cv2.resize(bird_eye_view_1, image_shape) AUGMENTATIONS_TEST = Compose([ diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_tf_lite.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py similarity index 88% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_tf_lite.py rename to behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py index 80d4a15c..328c7640 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_tf_lite.py +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py @@ -15,7 +15,7 @@ from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError @@ -24,9 +24,9 @@ import os os.environ['CUDA_VISIBLE_DEVICES'] = '-1' -gpus = tf.config.experimental.list_physical_devices('GPU') -for gpu in gpus: - tf.config.experimental.set_memory_growth(gpu, True) +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) class Brain: @@ -66,7 +66,7 @@ def __init__(self, sensors, actuators, handler, model, config=None): logger.info("Using TF lite models.....") self.net = tf.lite.Interpreter(model_path= PRETRAINED_MODELS + model) self.net.allocate_tensors() - self.input_index = self.net.get_input_details()[0]["index"] + self.input_index = self.net.get_input_details()[0] self.output_index = self.net.get_output_details()[0]["index"] self.inf_func = self.optim_inference @@ -89,12 +89,22 @@ def optim_inference(self, img): output -- prediction from the model """ # Pre-processing - self.net.set_tensor(self.input_index, img) + if self.net.get_input_details()[0]['dtype'] == np.uint8: + input_scale, input_zero_point = self.net.get_input_details()[0]["quantization"] + img = img / input_scale + input_zero_point + img = img.astype(self.net.get_input_details()[0]["dtype"]) + + self.net.set_tensor(self.input_index["index"], img.astype(self.input_index["dtype"])) # Run inference. self.net.invoke() # Post-processing output = self.net.get_tensor(self.output_index) + if self.net.get_input_details()[0]['dtype'] == np.uint8: + output_scale, input_zero_point = self.net.get_output_details()[0]["quantization"] + output = output.astype(np.float32) + output = (output - input_zero_point) * output_scale + return output def update_frame(self, frame_id, data): @@ -154,7 +164,7 @@ def execute(self): self.update_pose(self.pose.getPose3d()) - image_shape=(50, 150) + image_shape=(66, 200) img_base = cv2.resize(bird_eye_view_1, image_shape) AUGMENTATIONS_TEST = Compose([ diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py similarity index 99% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py rename to behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py index f62587e6..ae86a3c7 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py @@ -15,7 +15,7 @@ from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_70_km_h.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_70_km_h.py new file mode 100644 index 00000000..42240db9 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_70_km_h.py @@ -0,0 +1,299 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_speed = 0 + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + self.image_1 = 0 + self.image_2 = 0 + self.image_3 = 0 + self.image_4 = 0 + self.image_5 = 0 + self.image_6 = 0 + self.image_7 = 0 + self.image_8 = 0 + self.image_9 = 0 + + self.image_1_V = 0 + self.image_2_V = 0 + self.image_3_V = 0 + self.image_4_V = 0 + self.image_5_V = 0 + self.image_6_V = 0 + self.image_7_V = 0 + self.image_8_V = 0 + self.image_9_V = 0 + + self.first_acceleration = True + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + if type(self.image_1) is int: + self.image_1 = img + self.image_1_V = 0 + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_2) is int: + self.image_2 = img + self.image_2_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_3) is int: + self.image_3 = img + self.image_3_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_4) is int: + self.image_4 = img + self.image_4_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_5) is int: + self.image_5 = img + self.image_5_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_6) is int: + self.image_6 = img + self.image_6_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_7) is int: + self.image_7 = img + self.image_7_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_8) is int: + self.image_8 = img + self.image_8_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_9) is int: + self.image_9 = img + self.image_9_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + else: + self.image_1 = self.image_2 + self.image_2 = self.image_3 + self.image_3 = self.image_4 + self.image_4 = self.image_5 + self.image_5 = self.image_6 + self.image_6 = self.image_7 + self.image_7 = self.image_8 + self.image_8 = self.image_9 + self.image_9 = img + + self.image_1_V = self.image_2_V + self.image_2_V = self.image_3_V + self.image_3_V = self.image_4_V + self.image_4_V = self.image_5_V + self.image_5_V = self.image_6_V + self.image_6_V = self.image_7_V + self.image_7_V = self.image_8_V + self.image_8_V = self.image_9_V + self.image_9_V = self.previous_speed + + velocity_dim_1 = np.full((150, 50), self.image_1_V/30) + image_1 = np.dstack((self.image_1, velocity_dim_1)) + + velocity_dim_4 = np.full((150, 50), self.image_4_V/30) + image_4 = np.dstack((self.image_4, velocity_dim_4)) + + velocity_dim_9 = np.full((150, 50), self.image_9_V/30) + image_9 = np.dstack((self.image_9, velocity_dim_9)) + + img = [image_1, image_4 , image_9] + + img = np.expand_dims(img, axis=0) + + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + if vehicle_speed < 70 and self.first_acceleration: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.first_acceleration = False + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input.py new file mode 100644 index 00000000..373c55e8 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input.py @@ -0,0 +1,305 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout, ChannelDropout +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_speed = 0 + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + self.image_1 = 0 + self.image_2 = 0 + self.image_3 = 0 + self.image_4 = 0 + self.image_5 = 0 + self.image_6 = 0 + self.image_7 = 0 + self.image_8 = 0 + self.image_9 = 0 + + self.image_1_V = 0 + self.image_2_V = 0 + self.image_3_V = 0 + self.image_4_V = 0 + self.image_5_V = 0 + self.image_6_V = 0 + self.image_7_V = 0 + self.image_8_V = 0 + self.image_9_V = 0 + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + + AUGMENTATIONS_TEST = Compose([ + GridDropout(p=1.0, ratio=0.9) + ]) + + bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1) + bird_eye_view_1 = bird_eye_view_1["image"] + + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + if type(self.image_1) is int: + self.image_1 = img + self.image_1_V = 0 + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_2) is int: + self.image_2 = img + self.image_2_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_3) is int: + self.image_3 = img + self.image_3_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_4) is int: + self.image_4 = img + self.image_4_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_5) is int: + self.image_5 = img + self.image_5_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_6) is int: + self.image_6 = img + self.image_6_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_7) is int: + self.image_7 = img + self.image_7_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_8) is int: + self.image_8 = img + self.image_8_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_9) is int: + self.image_9 = img + self.image_9_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + else: + self.image_1 = self.image_2 + self.image_2 = self.image_3 + self.image_3 = self.image_4 + self.image_4 = self.image_5 + self.image_5 = self.image_6 + self.image_6 = self.image_7 + self.image_7 = self.image_8 + self.image_8 = self.image_9 + self.image_9 = img + + self.image_1_V = self.image_2_V + self.image_2_V = self.image_3_V + self.image_3_V = self.image_4_V + self.image_4_V = self.image_5_V + self.image_5_V = self.image_6_V + self.image_6_V = self.image_7_V + self.image_7_V = self.image_8_V + self.image_8_V = self.image_9_V + self.image_9_V = self.previous_speed + + velocity_dim_1 = np.full((150, 50), self.image_1_V/30) + image_1 = np.dstack((self.image_1, velocity_dim_1)) + + velocity_dim_4 = np.full((150, 50), self.image_4_V/30) + image_4 = np.dstack((self.image_4, velocity_dim_4)) + + velocity_dim_9 = np.full((150, 50), self.image_9_V/30) + image_9 = np.dstack((self.image_9, velocity_dim_9)) + + img = [image_1, image_4 , image_9] + + img = np.expand_dims(img, axis=0) + + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input_2.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input_2.py new file mode 100644 index 00000000..469d3055 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9_broken_input_2.py @@ -0,0 +1,306 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout, ChannelDropout, GaussNoise +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.previous_speed = 0 + self.previous_bird_eye_view_image = 0 + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + self.image_1 = 0 + self.image_2 = 0 + self.image_3 = 0 + self.image_4 = 0 + self.image_5 = 0 + self.image_6 = 0 + self.image_7 = 0 + self.image_8 = 0 + self.image_9 = 0 + + self.image_1_V = 0 + self.image_2_V = 0 + self.image_3_V = 0 + self.image_4_V = 0 + self.image_5_V = 0 + self.image_6_V = 0 + self.image_7_V = 0 + self.image_8_V = 0 + self.image_9_V = 0 + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + + AUGMENTATIONS_TEST = Compose([ + #GridDropout(p=1.0, ratio=0.5), + GaussNoise(p=1.0, var_limit=(500.0, 1500.0)) + ]) + + bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1) + bird_eye_view_1 = bird_eye_view_1["image"] + + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + self.bird_eye_view_images += 1 + if (self.previous_bird_eye_view_image==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.previous_bird_eye_view_image = img + + if type(self.image_1) is int: + self.image_1 = img + self.image_1_V = 0 + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_2) is int: + self.image_2 = img + self.image_2_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_3) is int: + self.image_3 = img + self.image_3_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_4) is int: + self.image_4 = img + self.image_4_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_5) is int: + self.image_5 = img + self.image_5_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_6) is int: + self.image_6 = img + self.image_6_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_7) is int: + self.image_7 = img + self.image_7_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_8) is int: + self.image_8 = img + self.image_8_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + elif type(self.image_9) is int: + self.image_9 = img + self.image_9_V = self.previous_speed + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + else: + self.image_1 = self.image_2 + self.image_2 = self.image_3 + self.image_3 = self.image_4 + self.image_4 = self.image_5 + self.image_5 = self.image_6 + self.image_6 = self.image_7 + self.image_7 = self.image_8 + self.image_8 = self.image_9 + self.image_9 = img + + self.image_1_V = self.image_2_V + self.image_2_V = self.image_3_V + self.image_3_V = self.image_4_V + self.image_4_V = self.image_5_V + self.image_5_V = self.image_6_V + self.image_6_V = self.image_7_V + self.image_7_V = self.image_8_V + self.image_8_V = self.image_9_V + self.image_9_V = self.previous_speed + + velocity_dim_1 = np.full((150, 50), self.image_1_V/30) + image_1 = np.dstack((self.image_1, velocity_dim_1)) + + velocity_dim_4 = np.full((150, 50), self.image_4_V/30) + image_4 = np.dstack((self.image_4, velocity_dim_4)) + + velocity_dim_9 = np.full((150, 50), self.image_9_V/30) + image_9 = np.dstack((self.image_9, velocity_dim_9)) + + img = [image_1, image_4 , image_9] + + img = np.expand_dims(img, axis=0) + + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + self.previous_speed = vehicle_speed + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + + + + + diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py similarity index 98% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py rename to behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py index 4082712e..8b895393 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py @@ -15,7 +15,7 @@ from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_70_km_h.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_70_km_h.py new file mode 100644 index 00000000..93ce6163 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_70_km_h.py @@ -0,0 +1,225 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.image_1 = 0 + self.image_2 = 0 + self.image_3 = 0 + self.image_4 = 0 + self.image_5 = 0 + self.image_6 = 0 + self.image_7 = 0 + self.image_8 = 0 + self.image_9 = 0 + self.image_10 = 0 + + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + self.first_acceleration = True + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + if type(self.image_1) is int: + self.image_1 = img + elif type(self.image_2) is int: + self.image_2 = img + elif type(self.image_3) is int: + self.image_3 = img + elif type(self.image_4) is int: + self.image_4 = img + elif type(self.image_5) is int: + self.image_5 = img + elif type(self.image_6) is int: + self.image_6 = img + elif type(self.image_7) is int: + self.image_7 = img + elif type(self.image_8) is int: + self.image_8 = img + elif type(self.image_9) is int: + self.image_9 = img + else: + self.bird_eye_view_images += 1 + if (self.image_9==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.image_1 = self.image_2 + self.image_2 = self.image_3 + self.image_3 = self.image_4 + self.image_4 = self.image_5 + self.image_5 = self.image_6 + self.image_6 = self.image_7 + self.image_7 = self.image_8 + self.image_8 = self.image_9 + self.image_9 = img + + img = [self.image_1, self.image_4, self.image_9] + img = np.expand_dims(img, axis=0) + + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed < 70 and self.first_acceleration: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) \ No newline at end of file diff --git a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_V_MAX_30.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_V_MAX_30.py similarity index 98% rename from behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_V_MAX_30.py rename to behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_V_MAX_30.py index 7451f324..db355b88 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_V_MAX_30.py +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_V_MAX_30.py @@ -15,7 +15,7 @@ from utils.logger import logger from traceback import print_exc -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'carla_tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' from tensorflow.python.framework.errors_impl import NotFoundError from tensorflow.python.framework.errors_impl import UnimplementedError @@ -239,7 +239,7 @@ def execute(self): self.motors.sendSteer(0.0) self.motors.sendBrake(0) else: - self.motors.sendThrottle(throttle) + self.motors.sendThrottle(0.75) self.motors.sendSteer(steer) self.motors.sendBrake(break_command) diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_broken_input.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_broken_input.py new file mode 100644 index 00000000..658e4ed0 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_broken_input.py @@ -0,0 +1,232 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + print(self.net.summary()) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.image_1 = 0 + self.image_2 = 0 + self.image_3 = 0 + self.image_4 = 0 + self.image_5 = 0 + self.image_6 = 0 + self.image_7 = 0 + self.image_8 = 0 + self.image_9 = 0 + self.image_10 = 0 + + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + + AUGMENTATIONS_TEST = Compose([ + GridDropout(p=1.0) + ]) + + bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1) + bird_eye_view_1 = bird_eye_view_1["image"] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + if type(self.image_1) is int: + self.image_1 = img + elif type(self.image_2) is int: + self.image_2 = img + elif type(self.image_3) is int: + self.image_3 = img + elif type(self.image_4) is int: + self.image_4 = img + elif type(self.image_5) is int: + self.image_5 = img + elif type(self.image_6) is int: + self.image_6 = img + elif type(self.image_7) is int: + self.image_7 = img + elif type(self.image_8) is int: + self.image_8 = img + elif type(self.image_9) is int: + self.image_9 = img + else: + self.bird_eye_view_images += 1 + if (self.image_9==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.image_1 = self.image_2 + self.image_2 = self.image_3 + self.image_3 = self.image_4 + self.image_4 = self.image_5 + self.image_5 = self.image_6 + self.image_6 = self.image_7 + self.image_7 = self.image_8 + self.image_8 = self.image_9 + self.image_9 = img + + img = [self.image_1, self.image_4, self.image_9] + img = np.expand_dims(img, axis=0) + + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) \ No newline at end of file diff --git a/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_broken_input_2.py b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_broken_input_2.py new file mode 100644 index 00000000..8ca03b11 --- /dev/null +++ b/behavior_metrics/brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9_broken_input_2.py @@ -0,0 +1,232 @@ +#!/usr/bin/python +# -*- coding: utf-8 -*- +import csv +import cv2 +import math +import numpy as np +import threading +import time +import carla +from os import path +from albumentations import ( + Compose, Normalize, RandomRain, RandomBrightness, RandomShadow, RandomSnow, RandomFog, RandomSunFlare, GridDropout +) +from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from utils.logger import logger +from traceback import print_exc + +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' + +from tensorflow.python.framework.errors_impl import NotFoundError +from tensorflow.python.framework.errors_impl import UnimplementedError +import tensorflow as tf + +import os +os.environ['CUDA_VISIBLE_DEVICES'] = '-1' + +#gpus = tf.config.experimental.list_physical_devices('GPU') +#for gpu in gpus: +# tf.config.experimental.set_memory_growth(gpu, True) + + + +class Brain: + + def __init__(self, sensors, actuators, handler, model, config=None): + self.camera_0 = sensors.get_camera('camera_0') + self.camera_1 = sensors.get_camera('camera_1') + self.camera_2 = sensors.get_camera('camera_2') + self.camera_3 = sensors.get_camera('camera_3') + + self.cameras_first_images = [] + + self.pose = sensors.get_pose3d('pose3d_0') + + self.bird_eye_view = sensors.get_bird_eye_view('bird_eye_view_0') + + self.motors = actuators.get_motor('motors_0') + self.handler = handler + self.config = config + self.inference_times = [] + self.gpu_inference = True if tf.test.gpu_device_name() else False + + self.threshold_image = np.zeros((640, 360, 3), np.uint8) + self.color_image = np.zeros((640, 360, 3), np.uint8) + + client = carla.Client('localhost', 2000) + client.set_timeout(10.0) # seconds + world = client.get_world() + + time.sleep(5) + self.vehicle = world.get_actors().filter('vehicle.*')[0] + + if model: + if not path.exists(PRETRAINED_MODELS + model): + logger.info("File " + model + " cannot be found in " + PRETRAINED_MODELS) + logger.info("** Load TF model **") + self.net = tf.keras.models.load_model(PRETRAINED_MODELS + model) + print(self.net.summary()) + logger.info("** Loaded TF model **") + else: + logger.info("** Brain not loaded **") + logger.info("- Models path: " + PRETRAINED_MODELS) + logger.info("- Model: " + str(model)) + + self.image_1 = 0 + self.image_2 = 0 + self.image_3 = 0 + self.image_4 = 0 + self.image_5 = 0 + self.image_6 = 0 + self.image_7 = 0 + self.image_8 = 0 + self.image_9 = 0 + self.image_10 = 0 + + self.bird_eye_view_images = 0 + self.bird_eye_view_unique_images = 0 + + + def update_frame(self, frame_id, data): + """Update the information to be shown in one of the GUI's frames. + + Arguments: + frame_id {str} -- Id of the frame that will represent the data + data {*} -- Data to be shown in the frame. Depending on the type of frame (rgbimage, laser, pose3d, etc) + """ + if data.shape[0] != data.shape[1]: + if data.shape[0] > data.shape[1]: + difference = data.shape[0] - data.shape[1] + extra_left, extra_right = int(difference/2), int(difference/2) + extra_top, extra_bottom = 0, 0 + else: + difference = data.shape[1] - data.shape[0] + extra_left, extra_right = 0, 0 + extra_top, extra_bottom = int(difference/2), int(difference/2) + + + data = np.pad(data, ((extra_top, extra_bottom), (extra_left, extra_right), (0, 0)), mode='constant', constant_values=0) + + self.handler.update_frame(frame_id, data) + + def update_pose(self, pose_data): + self.handler.update_pose3d(pose_data) + + def execute(self): + image = self.camera_0.getImage().data + image_1 = self.camera_1.getImage().data + image_2 = self.camera_2.getImage().data + image_3 = self.camera_3.getImage().data + + bird_eye_view_1 = self.bird_eye_view.getImage(self.vehicle) + bird_eye_view_1 = cv2.cvtColor(bird_eye_view_1, cv2.COLOR_BGR2RGB) + + if self.cameras_first_images == []: + self.cameras_first_images.append(image) + self.cameras_first_images.append(image_1) + self.cameras_first_images.append(image_2) + self.cameras_first_images.append(image_3) + self.cameras_first_images.append(bird_eye_view_1) + + self.cameras_last_images = [ + image, + image_1, + image_2, + image_3, + bird_eye_view_1 + ] + + + AUGMENTATIONS_TEST = Compose([ + GridDropout(p=1.0, ratio=0.9) + ]) + + bird_eye_view_1 = AUGMENTATIONS_TEST(image=bird_eye_view_1) + bird_eye_view_1 = bird_eye_view_1["image"] + + self.update_frame('frame_1', image_1) + self.update_frame('frame_2', image_2) + self.update_frame('frame_3', image_3) + + self.update_frame('frame_0', bird_eye_view_1) + + self.update_pose(self.pose.getPose3d()) + + image_shape=(50, 150) + img_base = cv2.resize(bird_eye_view_1, image_shape) + + AUGMENTATIONS_TEST = Compose([ + Normalize() + ]) + image = AUGMENTATIONS_TEST(image=img_base) + img = image["image"] + + if type(self.image_1) is int: + self.image_1 = img + elif type(self.image_2) is int: + self.image_2 = img + elif type(self.image_3) is int: + self.image_3 = img + elif type(self.image_4) is int: + self.image_4 = img + elif type(self.image_5) is int: + self.image_5 = img + elif type(self.image_6) is int: + self.image_6 = img + elif type(self.image_7) is int: + self.image_7 = img + elif type(self.image_8) is int: + self.image_8 = img + elif type(self.image_9) is int: + self.image_9 = img + else: + self.bird_eye_view_images += 1 + if (self.image_9==img).all() == False: + self.bird_eye_view_unique_images += 1 + self.image_1 = self.image_2 + self.image_2 = self.image_3 + self.image_3 = self.image_4 + self.image_4 = self.image_5 + self.image_5 = self.image_6 + self.image_6 = self.image_7 + self.image_7 = self.image_8 + self.image_8 = self.image_9 + self.image_9 = img + + img = [self.image_1, self.image_4, self.image_9] + img = np.expand_dims(img, axis=0) + + start_time = time.time() + try: + prediction = self.net.predict(img, verbose=0) + self.inference_times.append(time.time() - start_time) + throttle = prediction[0][0] + steer = prediction[0][1] * (1 - (-1)) + (-1) + break_command = prediction[0][2] + speed = self.vehicle.get_velocity() + vehicle_speed = 3.6 * math.sqrt(speed.x**2 + speed.y**2 + speed.z**2) + + if vehicle_speed < 5: + self.motors.sendThrottle(1.0) + self.motors.sendSteer(0.0) + self.motors.sendBrake(0) + else: + self.motors.sendThrottle(throttle) + self.motors.sendSteer(steer) + self.motors.sendBrake(break_command) + + except NotFoundError as ex: + logger.info('Error inside brain: NotFoundError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except UnimplementedError as ex: + logger.info('Error inside brain: UnimplementedError!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) + except Exception as ex: + logger.info('Error inside brain: Exception!') + logger.warning(type(ex).__name__) + print_exc() + raise Exception(ex) \ No newline at end of file diff --git a/behavior_metrics/brains/brains_handler.py b/behavior_metrics/brains/brains_handler.py index 3bbaaf75..084c5dcf 100755 --- a/behavior_metrics/brains/brains_handler.py +++ b/behavior_metrics/brains/brains_handler.py @@ -34,9 +34,13 @@ def __init__(self, sensors, actuators, brain_path, controller, model=None, confi def load_brain(self, path, model=None): path_split = path.split("/") - robot_type = path_split[-2] + robot_type = path_split[1] module_name = path_split[-1][:-3] # removing .py extension - import_name = 'brains.' + robot_type + '.' + module_name + if len(path_split) == 4: + framework = path_split[2] + import_name = 'brains.' + robot_type + '.' + framework + '.' + module_name + else: + import_name = 'brains.' + robot_type + '.' + module_name if robot_type == 'CARLA': module = importlib.import_module(import_name) diff --git a/behavior_metrics/brains/agents/f1/__init__.py b/behavior_metrics/brains/gazebo/agents/__init__.py similarity index 100% rename from behavior_metrics/brains/agents/f1/__init__.py rename to behavior_metrics/brains/gazebo/agents/__init__.py diff --git a/behavior_metrics/brains/agents/dqn.py b/behavior_metrics/brains/gazebo/agents/dqn.py similarity index 100% rename from behavior_metrics/brains/agents/dqn.py rename to behavior_metrics/brains/gazebo/agents/dqn.py diff --git a/behavior_metrics/brains/agents/f1/.env b/behavior_metrics/brains/gazebo/agents/f1/.env similarity index 100% rename from behavior_metrics/brains/agents/f1/.env rename to behavior_metrics/brains/gazebo/agents/f1/.env diff --git a/behavior_metrics/brains/agents/f1/.env.sample b/behavior_metrics/brains/gazebo/agents/f1/.env.sample similarity index 100% rename from behavior_metrics/brains/agents/f1/.env.sample rename to behavior_metrics/brains/gazebo/agents/f1/.env.sample diff --git a/behavior_metrics/brains/car/__init__.py b/behavior_metrics/brains/gazebo/agents/f1/__init__.py similarity index 100% rename from behavior_metrics/brains/car/__init__.py rename to behavior_metrics/brains/gazebo/agents/f1/__init__.py diff --git a/behavior_metrics/brains/agents/f1/dqn.py b/behavior_metrics/brains/gazebo/agents/f1/dqn.py similarity index 100% rename from behavior_metrics/brains/agents/f1/dqn.py rename to behavior_metrics/brains/gazebo/agents/f1/dqn.py diff --git a/behavior_metrics/brains/agents/f1/f1_follow_line_camera_dqn.py b/behavior_metrics/brains/gazebo/agents/f1/f1_follow_line_camera_dqn.py similarity index 100% rename from behavior_metrics/brains/agents/f1/f1_follow_line_camera_dqn.py rename to behavior_metrics/brains/gazebo/agents/f1/f1_follow_line_camera_dqn.py diff --git a/behavior_metrics/brains/agents/f1/f1_follow_line_qlearn.py b/behavior_metrics/brains/gazebo/agents/f1/f1_follow_line_qlearn.py similarity index 100% rename from behavior_metrics/brains/agents/f1/f1_follow_line_qlearn.py rename to behavior_metrics/brains/gazebo/agents/f1/f1_follow_line_qlearn.py diff --git a/behavior_metrics/brains/agents/f1/liveplot.py b/behavior_metrics/brains/gazebo/agents/f1/liveplot.py similarity index 100% rename from behavior_metrics/brains/agents/f1/liveplot.py rename to behavior_metrics/brains/gazebo/agents/f1/liveplot.py diff --git a/behavior_metrics/brains/agents/f1/memory.py b/behavior_metrics/brains/gazebo/agents/f1/memory.py similarity index 100% rename from behavior_metrics/brains/agents/f1/memory.py rename to behavior_metrics/brains/gazebo/agents/f1/memory.py diff --git a/behavior_metrics/brains/agents/f1/qlearn.py b/behavior_metrics/brains/gazebo/agents/f1/qlearn.py similarity index 100% rename from behavior_metrics/brains/agents/f1/qlearn.py rename to behavior_metrics/brains/gazebo/agents/f1/qlearn.py diff --git a/behavior_metrics/brains/agents/f1/ros_gazebo_pose.py b/behavior_metrics/brains/gazebo/agents/f1/ros_gazebo_pose.py similarity index 100% rename from behavior_metrics/brains/agents/f1/ros_gazebo_pose.py rename to behavior_metrics/brains/gazebo/agents/f1/ros_gazebo_pose.py diff --git a/behavior_metrics/brains/agents/f1/settings.py b/behavior_metrics/brains/gazebo/agents/f1/settings.py similarity index 100% rename from behavior_metrics/brains/agents/f1/settings.py rename to behavior_metrics/brains/gazebo/agents/f1/settings.py diff --git a/behavior_metrics/brains/agents/f1_follow_line_camera_dqn.py b/behavior_metrics/brains/gazebo/agents/f1_follow_line_camera_dqn.py similarity index 100% rename from behavior_metrics/brains/agents/f1_follow_line_camera_dqn.py rename to behavior_metrics/brains/gazebo/agents/f1_follow_line_camera_dqn.py diff --git a/behavior_metrics/brains/agents/f1_follow_line_qlearn.py b/behavior_metrics/brains/gazebo/agents/f1_follow_line_qlearn.py similarity index 100% rename from behavior_metrics/brains/agents/f1_follow_line_qlearn.py rename to behavior_metrics/brains/gazebo/agents/f1_follow_line_qlearn.py diff --git a/behavior_metrics/brains/agents/liveplot.py b/behavior_metrics/brains/gazebo/agents/liveplot.py similarity index 100% rename from behavior_metrics/brains/agents/liveplot.py rename to behavior_metrics/brains/gazebo/agents/liveplot.py diff --git a/behavior_metrics/brains/agents/memory.py b/behavior_metrics/brains/gazebo/agents/memory.py similarity index 100% rename from behavior_metrics/brains/agents/memory.py rename to behavior_metrics/brains/gazebo/agents/memory.py diff --git a/behavior_metrics/brains/agents/qlearn.py b/behavior_metrics/brains/gazebo/agents/qlearn.py similarity index 100% rename from behavior_metrics/brains/agents/qlearn.py rename to behavior_metrics/brains/gazebo/agents/qlearn.py diff --git a/behavior_metrics/brains/agents/ros_gazebo_pose.py b/behavior_metrics/brains/gazebo/agents/ros_gazebo_pose.py similarity index 100% rename from behavior_metrics/brains/agents/ros_gazebo_pose.py rename to behavior_metrics/brains/gazebo/agents/ros_gazebo_pose.py diff --git a/behavior_metrics/brains/agents/scripts/benchmark_runner b/behavior_metrics/brains/gazebo/agents/scripts/benchmark_runner similarity index 100% rename from behavior_metrics/brains/agents/scripts/benchmark_runner rename to behavior_metrics/brains/gazebo/agents/scripts/benchmark_runner diff --git a/behavior_metrics/brains/agents/settings.py b/behavior_metrics/brains/gazebo/agents/settings.py similarity index 100% rename from behavior_metrics/brains/agents/settings.py rename to behavior_metrics/brains/gazebo/agents/settings.py diff --git a/behavior_metrics/brains/agents/turtlebot/circuit2_turtlebot_lidar_qlearn.py b/behavior_metrics/brains/gazebo/agents/turtlebot/circuit2_turtlebot_lidar_qlearn.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/circuit2_turtlebot_lidar_qlearn.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/circuit2_turtlebot_lidar_qlearn.py diff --git a/behavior_metrics/brains/agents/turtlebot/circuit2c_turtlebot_camera_dqn.py b/behavior_metrics/brains/gazebo/agents/turtlebot/circuit2c_turtlebot_camera_dqn.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/circuit2c_turtlebot_camera_dqn.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/circuit2c_turtlebot_camera_dqn.py diff --git a/behavior_metrics/brains/agents/turtlebot/deepq.py b/behavior_metrics/brains/gazebo/agents/turtlebot/deepq.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/deepq.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/deepq.py diff --git a/behavior_metrics/brains/agents/turtlebot/liveplot.py b/behavior_metrics/brains/gazebo/agents/turtlebot/liveplot.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/liveplot.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/liveplot.py diff --git a/behavior_metrics/brains/agents/turtlebot/memory.py b/behavior_metrics/brains/gazebo/agents/turtlebot/memory.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/memory.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/memory.py diff --git a/behavior_metrics/brains/agents/turtlebot/qlearn.py b/behavior_metrics/brains/gazebo/agents/turtlebot/qlearn.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/qlearn.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/qlearn.py diff --git a/behavior_metrics/brains/agents/turtlebot/round_turtlebot_lidar_test.py b/behavior_metrics/brains/gazebo/agents/turtlebot/round_turtlebot_lidar_test.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/round_turtlebot_lidar_test.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/round_turtlebot_lidar_test.py diff --git a/behavior_metrics/brains/agents/turtlebot/runtraining_dqn_circuit2_turtlebot_lidar.py b/behavior_metrics/brains/gazebo/agents/turtlebot/runtraining_dqn_circuit2_turtlebot_lidar.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/runtraining_dqn_circuit2_turtlebot_lidar.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/runtraining_dqn_circuit2_turtlebot_lidar.py diff --git a/behavior_metrics/brains/agents/turtlebot/sarsa.py b/behavior_metrics/brains/gazebo/agents/turtlebot/sarsa.py similarity index 100% rename from behavior_metrics/brains/agents/turtlebot/sarsa.py rename to behavior_metrics/brains/gazebo/agents/turtlebot/sarsa.py diff --git a/behavior_metrics/brains/agents/utilities/averaged_table.py b/behavior_metrics/brains/gazebo/agents/utilities/averaged_table.py similarity index 100% rename from behavior_metrics/brains/agents/utilities/averaged_table.py rename to behavior_metrics/brains/gazebo/agents/utilities/averaged_table.py diff --git a/behavior_metrics/brains/agents/utilities/camera_visualizer.py b/behavior_metrics/brains/gazebo/agents/utilities/camera_visualizer.py similarity index 100% rename from behavior_metrics/brains/agents/utilities/camera_visualizer.py rename to behavior_metrics/brains/gazebo/agents/utilities/camera_visualizer.py diff --git a/behavior_metrics/brains/agents/utilities/display_plot.py b/behavior_metrics/brains/gazebo/agents/utilities/display_plot.py similarity index 100% rename from behavior_metrics/brains/agents/utilities/display_plot.py rename to behavior_metrics/brains/gazebo/agents/utilities/display_plot.py diff --git a/behavior_metrics/brains/drone/__init__.py b/behavior_metrics/brains/gazebo/car/__init__.py similarity index 100% rename from behavior_metrics/brains/drone/__init__.py rename to behavior_metrics/brains/gazebo/car/__init__.py diff --git a/behavior_metrics/brains/car/brain_car_opencv2.py b/behavior_metrics/brains/gazebo/car/brain_car_opencv2.py similarity index 100% rename from behavior_metrics/brains/car/brain_car_opencv2.py rename to behavior_metrics/brains/gazebo/car/brain_car_opencv2.py diff --git a/behavior_metrics/brains/f1/__init__.py b/behavior_metrics/brains/gazebo/drone/__init__.py old mode 100755 new mode 100644 similarity index 100% rename from behavior_metrics/brains/f1/__init__.py rename to behavior_metrics/brains/gazebo/drone/__init__.py diff --git a/behavior_metrics/brains/drone/brain_drone_explicit.py b/behavior_metrics/brains/gazebo/drone/brain_drone_explicit.py similarity index 100% rename from behavior_metrics/brains/drone/brain_drone_explicit.py rename to behavior_metrics/brains/gazebo/drone/brain_drone_explicit.py diff --git a/behavior_metrics/brains/f1/torch_utils/__init__.py b/behavior_metrics/brains/gazebo/f1/__init__.py old mode 100644 new mode 100755 similarity index 100% rename from behavior_metrics/brains/f1/torch_utils/__init__.py rename to behavior_metrics/brains/gazebo/f1/__init__.py diff --git a/behavior_metrics/brains/f1/brain_f1_dummy.py b/behavior_metrics/brains/gazebo/f1/brain_f1_dummy.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_dummy.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_dummy.py diff --git a/behavior_metrics/brains/f1/brain_f1_explicit.py b/behavior_metrics/brains/gazebo/f1/brain_f1_explicit.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_explicit.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_explicit.py diff --git a/behavior_metrics/brains/f1/brain_f1_follow_line_dqn.py b/behavior_metrics/brains/gazebo/f1/brain_f1_follow_line_dqn.py similarity index 97% rename from behavior_metrics/brains/f1/brain_f1_follow_line_dqn.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_follow_line_dqn.py index b3ba8397..8c026bf3 100644 --- a/behavior_metrics/brains/f1/brain_f1_follow_line_dqn.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_follow_line_dqn.py @@ -1,7 +1,7 @@ import tensorflow as tf from gym.envs.registration import register -from brains.f1.rl_utils.inference import InferencerWrapper +from brains.gazebo.f1.rl_utils.inference import InferencerWrapper import yaml import gym import numpy as np @@ -11,7 +11,7 @@ if 'F1Env-v0' not in gym.envs.registry.env_specs: gym.envs.register( id='F1Env-v0', - entry_point='brains.f1.rl_utils.models:F1Env', + entry_point='brains.gazebo.f1.rl_utils.models:F1Env', # More arguments here ) else: @@ -154,7 +154,7 @@ def __init__(self, sensors, actuators, handler, config=None): 'algorithm': 'dqn', 'environment': 'simple', 'agent': 'f1', - 'filename': 'brains/f1/config/config_inference_followline_dqn_f1_gazebo.yaml' + 'filename': 'brains/gazebo/f1/config/config_inference_followline_dqn_f1_gazebo.yaml' } f = open(args['filename'], "r") diff --git a/behavior_metrics/brains/f1/brain_f1_follow_line_qlearn.py b/behavior_metrics/brains/gazebo/f1/brain_f1_follow_line_qlearn.py similarity index 95% rename from behavior_metrics/brains/f1/brain_f1_follow_line_qlearn.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_follow_line_qlearn.py index d79ca355..b29471ff 100644 --- a/behavior_metrics/brains/f1/brain_f1_follow_line_qlearn.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_follow_line_qlearn.py @@ -7,14 +7,14 @@ import gym from gym.envs.registration import register -from brains.f1.rl_utils.inference import InferencerWrapper +from brains.gazebo.f1.rl_utils.inference import InferencerWrapper # F1 envs if 'F1Env-v0' not in gym.envs.registry.env_specs: gym.envs.register( id='F1Env-v0', - entry_point='brains.f1.rl_utils.models:F1Env', + entry_point='brains.gazebo.f1.rl_utils.models:F1Env', # More arguments here ) else: @@ -44,7 +44,7 @@ def __init__(self, sensors, actuators, handler, config=None): 'algorithm': 'qlearn', 'environment': 'simple', 'agent': 'f1', - 'filename': 'brains/f1/config/config_f1_qlearn.yaml' + 'filename': 'brains/gazebo/sf1/config/config_f1_qlearn.yaml' } f = open(args['filename'], "r") diff --git a/behavior_metrics/brains/f1/brain_f1_keras-lstm.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras-lstm.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras-lstm.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras-lstm.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras.py similarity index 98% rename from behavior_metrics/brains/f1/brain_f1_keras.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras.py index 3e38f5f5..c63d797c 100644 --- a/behavior_metrics/brains/f1/brain_f1_keras.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_keras.py @@ -22,7 +22,7 @@ ) from utils.gradcam.gradcam import GradCAM -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'gazebo/tf_models/' class Brain: diff --git a/behavior_metrics/brains/f1/brain_f1_keras_classification-bw.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_classification-bw.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_classification-bw.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_classification-bw.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_classification.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_classification.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_classification.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_classification.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_opencv_dataset.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_opencv_dataset.py similarity index 99% rename from behavior_metrics/brains/f1/brain_f1_keras_opencv_dataset.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_opencv_dataset.py index 7cfecf60..aad859fa 100644 --- a/behavior_metrics/brains/f1/brain_f1_keras_opencv_dataset.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_opencv_dataset.py @@ -22,7 +22,7 @@ from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH from utils.gradcam.gradcam import GradCAM -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'gazebo/tf_models/' class Brain: diff --git a/behavior_metrics/brains/f1/brain_f1_keras_preprocessed.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_preprocessed.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_preprocessed_lstm.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_lstm.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_preprocessed_lstm.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_lstm.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_preprocessed_lstm_3_elements-60pts.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_lstm_3_elements-60pts.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_preprocessed_lstm_3_elements-60pts.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_lstm_3_elements-60pts.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_preprocessed_lstm_3_elements.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_lstm_3_elements.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_preprocessed_lstm_3_elements.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_lstm_3_elements.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_preprocessed_lstm_5_elements.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_lstm_5_elements.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_preprocessed_lstm_5_elements.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_lstm_5_elements.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_preprocessed_v_w.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_v_w.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_preprocessed_v_w.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_preprocessed_v_w.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_scripting.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_scripting.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_keras_scripting.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_scripting.py diff --git a/behavior_metrics/brains/f1/brain_f1_keras_seq_3.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_seq_3.py similarity index 98% rename from behavior_metrics/brains/f1/brain_f1_keras_seq_3.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_seq_3.py index 316f7a22..f3ee5366 100644 --- a/behavior_metrics/brains/f1/brain_f1_keras_seq_3.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_seq_3.py @@ -23,7 +23,7 @@ ) from utils.gradcam.gradcam import GradCAM -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'gazebo/tf_models/' class Brain: diff --git a/behavior_metrics/brains/f1/brain_f1_keras_seq_3_opencv_dataset.py b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_seq_3_opencv_dataset.py similarity index 99% rename from behavior_metrics/brains/f1/brain_f1_keras_seq_3_opencv_dataset.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_keras_seq_3_opencv_dataset.py index a9ff4d1a..4883e117 100644 --- a/behavior_metrics/brains/f1/brain_f1_keras_seq_3_opencv_dataset.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_keras_seq_3_opencv_dataset.py @@ -22,7 +22,7 @@ from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH from utils.gradcam.gradcam import GradCAM -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'tf_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'gazebo/tf_models/' class Brain: diff --git a/behavior_metrics/brains/f1/brain_f1_opencv.py b/behavior_metrics/brains/gazebo/f1/brain_f1_opencv.py similarity index 100% rename from behavior_metrics/brains/f1/brain_f1_opencv.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_opencv.py diff --git a/behavior_metrics/brains/f1/brain_f1_torch-lstm.py b/behavior_metrics/brains/gazebo/f1/brain_f1_torch-lstm.py similarity index 95% rename from behavior_metrics/brains/f1/brain_f1_torch-lstm.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_torch-lstm.py index 1e36b511..2b047f8c 100644 --- a/behavior_metrics/brains/f1/brain_f1_torch-lstm.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_torch-lstm.py @@ -17,7 +17,7 @@ import time import os from PIL import Image -from brains.f1.torch_utils.deepest_lstm_tinypilotnet import DeepestLSTMTinyPilotNet +from brains.gazebo.f1.torch_utils.deepest_lstm_tinypilotnet import DeepestLSTMTinyPilotNet from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH from os import path from albumentations import ( @@ -25,7 +25,7 @@ ) -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'torch_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'gazebo/torch_models/' FLOAT = torch.FloatTensor class Brain: diff --git a/behavior_metrics/brains/f1/brain_f1_torch.py b/behavior_metrics/brains/gazebo/f1/brain_f1_torch.py similarity index 97% rename from behavior_metrics/brains/f1/brain_f1_torch.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_torch.py index 82dd283a..a37f98a0 100644 --- a/behavior_metrics/brains/f1/brain_f1_torch.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_torch.py @@ -17,11 +17,11 @@ import time import os from PIL import Image -from brains.f1.torch_utils.pilotnet import PilotNet +from brains.gazebo.f1.torch_utils.pilotnet import PilotNet from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH from os import path -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'torch_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'gazebo/torch_models/' FLOAT = torch.FloatTensor class Brain: diff --git a/behavior_metrics/brains/f1/brain_f1_torchstacked.py b/behavior_metrics/brains/gazebo/f1/brain_f1_torchstacked.py similarity index 97% rename from behavior_metrics/brains/f1/brain_f1_torchstacked.py rename to behavior_metrics/brains/gazebo/f1/brain_f1_torchstacked.py index 68c15905..f4d20a1c 100644 --- a/behavior_metrics/brains/f1/brain_f1_torchstacked.py +++ b/behavior_metrics/brains/gazebo/f1/brain_f1_torchstacked.py @@ -17,12 +17,12 @@ import time import os from PIL import Image -from brains.f1.torch_utils.pilotnetStacked import PilotNet +from brains.gazebo.f1.torch_utils.pilotnetStacked import PilotNet from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH from os import path from collections import deque -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'torch_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'gazebo/torch_models/' FLOAT = torch.FloatTensor class Brain: diff --git a/behavior_metrics/brains/f1/config/config_f1_qlearn.yaml b/behavior_metrics/brains/gazebo/f1/config/config_f1_qlearn.yaml similarity index 74% rename from behavior_metrics/brains/f1/config/config_f1_qlearn.yaml rename to behavior_metrics/brains/gazebo/f1/config/config_f1_qlearn.yaml index 53b9b957..d5e06329 100644 --- a/behavior_metrics/brains/f1/config/config_f1_qlearn.yaml +++ b/behavior_metrics/brains/gazebo/f1/config/config_f1_qlearn.yaml @@ -33,8 +33,8 @@ environments: inference: qlearn: - inference_file: models/rl_models/qlearn/20230216-170351_Circuit-simple_States-sp1_Actions-simple_Rewards-followline_center_epsilon-0.05_epoch-4751_step-15001_reward-139266-qtable.npy - actions_file: models/rl_models/actions_set_20221128_0938 + inference_file: models/gazebo/rl_models/qlearn/20230216-170351_Circuit-simple_States-sp1_Actions-simple_Rewards-followline_center_epsilon-0.05_epoch-4751_step-15001_reward-139266-qtable.npy + actions_file: models/gazebo/rl_models/actions_set_20221128_0938 algorithm: qlearn: diff --git a/behavior_metrics/brains/f1/config/config_inference_followline_dqn_f1_gazebo.yaml b/behavior_metrics/brains/gazebo/f1/config/config_inference_followline_dqn_f1_gazebo.yaml similarity index 96% rename from behavior_metrics/brains/f1/config/config_inference_followline_dqn_f1_gazebo.yaml rename to behavior_metrics/brains/gazebo/f1/config/config_inference_followline_dqn_f1_gazebo.yaml index 2f180f24..1f189826 100644 --- a/behavior_metrics/brains/f1/config/config_inference_followline_dqn_f1_gazebo.yaml +++ b/behavior_metrics/brains/gazebo/f1/config/config_inference_followline_dqn_f1_gazebo.yaml @@ -26,7 +26,7 @@ retraining: inference: dqn: - inference_file: models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model + inference_file: models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model algorithm: dqn: diff --git a/behavior_metrics/brains/f1/rl_utils/algorithms/__init__.py b/behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/__init__.py similarity index 69% rename from behavior_metrics/brains/f1/rl_utils/algorithms/__init__.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/__init__.py index e13d6709..f43387af 100644 --- a/behavior_metrics/brains/f1/rl_utils/algorithms/__init__.py +++ b/behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/__init__.py @@ -1,6 +1,6 @@ -from brains.f1.rl_utils.algorithms.algorithms_type import AlgorithmsType -from brains.f1.rl_utils.algorithms.qlearn_f1 import QLearnF1 -from brains.f1.rl_utils.algorithms.dqn_f1 import DQNF1 +from brains.gazebo.f1.rl_utils.algorithms.algorithms_type import AlgorithmsType +from brains.gazebo.f1.rl_utils.algorithms.qlearn_f1 import QLearnF1 +from brains.gazebo.f1.rl_utils.algorithms.dqn_f1 import DQNF1 class InferencerFactory: def __new__(cls, config): diff --git a/behavior_metrics/brains/f1/rl_utils/algorithms/algorithms_type.py b/behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/algorithms_type.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/algorithms/algorithms_type.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/algorithms_type.py diff --git a/behavior_metrics/brains/f1/rl_utils/algorithms/dqn_f1.py b/behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/dqn_f1.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/algorithms/dqn_f1.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/dqn_f1.py diff --git a/behavior_metrics/brains/f1/rl_utils/algorithms/exceptions.py b/behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/exceptions.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/algorithms/exceptions.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/exceptions.py diff --git a/behavior_metrics/brains/f1/rl_utils/algorithms/loaders.py b/behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/loaders.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/algorithms/loaders.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/loaders.py diff --git a/behavior_metrics/brains/f1/rl_utils/algorithms/qlearn_f1.py b/behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/qlearn_f1.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/algorithms/qlearn_f1.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/algorithms/qlearn_f1.py diff --git a/behavior_metrics/brains/f1/rl_utils/env_type.py b/behavior_metrics/brains/gazebo/f1/rl_utils/env_type.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/env_type.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/env_type.py diff --git a/behavior_metrics/brains/f1/rl_utils/exceptions.py b/behavior_metrics/brains/gazebo/f1/rl_utils/exceptions.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/exceptions.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/exceptions.py diff --git a/behavior_metrics/brains/f1/rl_utils/gazebo_envs.py b/behavior_metrics/brains/gazebo/f1/rl_utils/gazebo_envs.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/gazebo_envs.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/gazebo_envs.py diff --git a/behavior_metrics/brains/f1/rl_utils/image_f1.py b/behavior_metrics/brains/gazebo/f1/rl_utils/image_f1.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/image_f1.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/image_f1.py diff --git a/behavior_metrics/brains/f1/rl_utils/inference.py b/behavior_metrics/brains/gazebo/f1/rl_utils/inference.py similarity index 93% rename from behavior_metrics/brains/f1/rl_utils/inference.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/inference.py index bebdf83b..87c39b61 100644 --- a/behavior_metrics/brains/f1/rl_utils/inference.py +++ b/behavior_metrics/brains/gazebo/f1/rl_utils/inference.py @@ -1,6 +1,6 @@ from pydantic import BaseModel -from brains.f1.rl_utils.algorithms import InferencerFactory +from brains.gazebo.f1.rl_utils.algorithms import InferencerFactory diff --git a/behavior_metrics/brains/f1/rl_utils/models/__init__.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/__init__.py similarity index 58% rename from behavior_metrics/brains/f1/rl_utils/models/__init__.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/__init__.py index 52ca30b6..38e16346 100644 --- a/behavior_metrics/brains/f1/rl_utils/models/__init__.py +++ b/behavior_metrics/brains/gazebo/f1/rl_utils/models/__init__.py @@ -1,7 +1,7 @@ -from brains.f1.rl_utils.env_type import EnvironmentType -from brains.f1.rl_utils.exceptions import NoValidEnvironmentType -from brains.f1.rl_utils.models.f1_env_camera import QlearnF1FollowLineEnvGazebo -from brains.f1.rl_utils.models.followline_dqn_tf import FollowLineDQNF1GazeboTF +from brains.gazebo.f1.rl_utils.env_type import EnvironmentType +from brains.gazebo.f1.rl_utils.exceptions import NoValidEnvironmentType +from brains.gazebo.f1.rl_utils.models.f1_env_camera import QlearnF1FollowLineEnvGazebo +from brains.gazebo.f1.rl_utils.models.followline_dqn_tf import FollowLineDQNF1GazeboTF class F1Env: diff --git a/behavior_metrics/brains/f1/rl_utils/models/f1_env.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/f1_env.py similarity index 95% rename from behavior_metrics/brains/f1/rl_utils/models/f1_env.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/f1_env.py index 21400071..89c72722 100644 --- a/behavior_metrics/brains/f1/rl_utils/models/f1_env.py +++ b/behavior_metrics/brains/gazebo/f1/rl_utils/models/f1_env.py @@ -4,7 +4,7 @@ from std_srvs.srv import Empty import numpy as np -from brains.f1.rl_utils import gazebo_envs +from brains.gazebo.f1.rl_utils import gazebo_envs class F1Env(gazebo_envs.GazeboEnv): diff --git a/behavior_metrics/brains/f1/rl_utils/models/f1_env_camera.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/f1_env_camera.py similarity index 95% rename from behavior_metrics/brains/f1/rl_utils/models/f1_env_camera.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/f1_env_camera.py index 41b065d9..be771783 100644 --- a/behavior_metrics/brains/f1/rl_utils/models/f1_env_camera.py +++ b/behavior_metrics/brains/gazebo/f1/rl_utils/models/f1_env_camera.py @@ -9,9 +9,9 @@ from gym import spaces from sensor_msgs.msg import Image -from brains.f1.rl_utils.settings import QLearnConfig -from brains.f1.rl_utils.image_f1 import ListenerCamera -from brains.f1.rl_utils.models.f1_env import F1Env +from brains.gazebo.f1.rl_utils.settings import QLearnConfig +from brains.gazebo.f1.rl_utils.image_f1 import ListenerCamera +from brains.gazebo.f1.rl_utils.models.f1_env import F1Env diff --git a/behavior_metrics/brains/f1/rl_utils/models/followline_dqn_tf.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/followline_dqn_tf.py similarity index 95% rename from behavior_metrics/brains/f1/rl_utils/models/followline_dqn_tf.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/followline_dqn_tf.py index 75856e3c..00905978 100644 --- a/behavior_metrics/brains/f1/rl_utils/models/followline_dqn_tf.py +++ b/behavior_metrics/brains/gazebo/f1/rl_utils/models/followline_dqn_tf.py @@ -9,7 +9,7 @@ from geometry_msgs.msg import Twist import numpy as np -from brains.f1.rl_utils.models.f1_env import F1Env +from brains.gazebo.f1.rl_utils.models.f1_env import F1Env from .settings import F1GazeboTFConfig diff --git a/behavior_metrics/brains/f1/rl_utils/models/images.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/images.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/models/images.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/images.py diff --git a/behavior_metrics/brains/f1/rl_utils/models/reset.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/reset.py similarity index 97% rename from behavior_metrics/brains/f1/rl_utils/models/reset.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/reset.py index bf756610..d286e015 100644 --- a/behavior_metrics/brains/f1/rl_utils/models/reset.py +++ b/behavior_metrics/brains/gazebo/f1/rl_utils/models/reset.py @@ -1,6 +1,6 @@ import numpy as np -from brains.f1.rl_utils.models.f1_env import F1Env +from brains.gazebo.f1.rl_utils.models.f1_env import F1Env class Reset(F1Env): diff --git a/behavior_metrics/brains/f1/rl_utils/models/rewards.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/rewards.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/models/rewards.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/rewards.py diff --git a/behavior_metrics/brains/f1/rl_utils/models/settings.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/settings.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/models/settings.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/settings.py diff --git a/behavior_metrics/brains/f1/rl_utils/models/simplified_perception.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/simplified_perception.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/models/simplified_perception.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/simplified_perception.py diff --git a/behavior_metrics/brains/f1/rl_utils/models/step.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/step.py similarity index 99% rename from behavior_metrics/brains/f1/rl_utils/models/step.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/step.py index 5e619801..94902bf2 100644 --- a/behavior_metrics/brains/f1/rl_utils/models/step.py +++ b/behavior_metrics/brains/gazebo/f1/rl_utils/models/step.py @@ -1,7 +1,7 @@ from geometry_msgs.msg import Twist import numpy as np import time -from brains.f1.rl_utils.models.f1_env import F1Env +from brains.gazebo.f1.rl_utils.models.f1_env import F1Env class StepFollowLine(F1Env): diff --git a/behavior_metrics/brains/f1/rl_utils/models/utils.py b/behavior_metrics/brains/gazebo/f1/rl_utils/models/utils.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/models/utils.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/models/utils.py diff --git a/behavior_metrics/brains/f1/rl_utils/settings.py b/behavior_metrics/brains/gazebo/f1/rl_utils/settings.py similarity index 100% rename from behavior_metrics/brains/f1/rl_utils/settings.py rename to behavior_metrics/brains/gazebo/f1/rl_utils/settings.py diff --git a/behavior_metrics/brains/f1rl/__init__.py b/behavior_metrics/brains/gazebo/f1/torch_utils/__init__.py similarity index 100% rename from behavior_metrics/brains/f1rl/__init__.py rename to behavior_metrics/brains/gazebo/f1/torch_utils/__init__.py diff --git a/behavior_metrics/brains/gazebo/f1/torch_utils/convlstm.py b/behavior_metrics/brains/gazebo/f1/torch_utils/convlstm.py new file mode 100644 index 00000000..678caa74 --- /dev/null +++ b/behavior_metrics/brains/gazebo/f1/torch_utils/convlstm.py @@ -0,0 +1,195 @@ +""" +This implementation of Convolutional LSTM has been adapted from https://github.com/ndrplz/ConvLSTM_pytorch. +""" + +import torch.nn as nn +import torch + + +class ConvLSTMCell(nn.Module): + + def __init__(self, input_dim, hidden_dim, kernel_size, bias): + """ + Initialize ConvLSTM cell. + + Parameters + ---------- + input_dim: int + Number of channels of input tensor. + hidden_dim: int + Number of channels of hidden state. + kernel_size: (int, int) + Size of the convolutional kernel. + bias: bool + Whether or not to add the bias. + """ + + super(ConvLSTMCell, self).__init__() + + self.input_dim = input_dim + self.hidden_dim = hidden_dim + + self.kernel_size = kernel_size + self.padding = kernel_size[0] // 2, kernel_size[1] // 2 + self.bias = bias + + self.conv = nn.Conv2d(in_channels=self.input_dim + self.hidden_dim, + out_channels=4 * self.hidden_dim, + kernel_size=self.kernel_size, + padding=self.padding, + bias=self.bias) + + def forward(self, input_tensor, cur_state): + h_cur, c_cur = cur_state + + combined = torch.cat([input_tensor, h_cur], dim=1) # concatenate along channel axis + + combined_conv = self.conv(combined) + cc_i, cc_f, cc_o, cc_g = torch.split(combined_conv, self.hidden_dim, dim=1) + i = torch.sigmoid(cc_i) + f = torch.sigmoid(cc_f) + o = torch.sigmoid(cc_o) + g = torch.tanh(cc_g) + + c_next = f * c_cur + i * g + h_next = o * torch.tanh(c_next) + + return h_next, c_next + + def init_hidden(self, batch_size, image_size): + height, width = image_size + return (torch.zeros(batch_size, self.hidden_dim, height, width, device=self.conv.weight.device), + torch.zeros(batch_size, self.hidden_dim, height, width, device=self.conv.weight.device)) + + +class ConvLSTM(nn.Module): + + """ + + Parameters: + input_dim: Number of channels in input + hidden_dim: Number of hidden channels + kernel_size: Size of kernel in convolutions + num_layers: Number of LSTM layers stacked on each other + batch_first: Whether or not dimension 0 is the batch or not + bias: Bias or no bias in Convolution + return_all_layers: Return the list of computations for all layers + Note: Will do same padding. + + Input: + A tensor of size B, T, C, H, W or T, B, C, H, W + Output: + A tuple of two lists of length num_layers (or length 1 if return_all_layers is False). + 0 - layer_output_list is the list of lists of length T of each output + 1 - last_state_list is the list of last states + each element of the list is a tuple (h, c) for hidden state and memory + Example: + >> x = torch.rand((32, 10, 64, 128, 128)) + >> convlstm = ConvLSTM(64, 16, 3, 1, True, True, False) + >> _, last_states = convlstm(x) + >> h = last_states[0][0] # 0 for layer index, 0 for h index + """ + + def __init__(self, input_dim, hidden_dim, kernel_size, num_layers, + batch_first=False, bias=True, return_all_layers=False): + super(ConvLSTM, self).__init__() + + self._check_kernel_size_consistency(kernel_size) + + # Make sure that both `kernel_size` and `hidden_dim` are lists having len == num_layers + kernel_size = self._extend_for_multilayer(kernel_size, num_layers) + hidden_dim = self._extend_for_multilayer(hidden_dim, num_layers) + if not len(kernel_size) == len(hidden_dim) == num_layers: + raise ValueError('Inconsistent list length.') + + self.input_dim = input_dim + self.hidden_dim = hidden_dim + self.kernel_size = kernel_size + self.num_layers = num_layers + self.batch_first = batch_first + self.bias = bias + self.return_all_layers = return_all_layers + + cell_list = [] + for i in range(0, self.num_layers): + cur_input_dim = self.input_dim if i == 0 else self.hidden_dim[i - 1] + + cell_list.append(ConvLSTMCell(input_dim=cur_input_dim, + hidden_dim=self.hidden_dim[i], + kernel_size=self.kernel_size[i], + bias=self.bias)) + + self.cell_list = nn.ModuleList(cell_list) + + def forward(self, input_tensor, hidden_state=None): + """ + + Parameters + ---------- + input_tensor: todo + 5-D Tensor either of shape (t, b, c, h, w) or (b, t, c, h, w) + hidden_state: todo + None. todo implement stateful + + Returns + ------- + last_state_list, layer_output + """ + if not self.batch_first: + # (t, b, c, h, w) -> (b, t, c, h, w) + input_tensor = input_tensor.permute(1, 0, 2, 3, 4) + + b, _, _, h, w = input_tensor.size() + + # Implement stateful ConvLSTM + if hidden_state is not None: + raise NotImplementedError() + else: + # Since the init is done in forward. Can send image size here + hidden_state = self._init_hidden(batch_size=b, + image_size=(h, w)) + + layer_output_list = [] + last_state_list = [] + + seq_len = input_tensor.size(1) + cur_layer_input = input_tensor + + for layer_idx in range(self.num_layers): + + h, c = hidden_state[layer_idx] + output_inner = [] + for t in range(seq_len): + h, c = self.cell_list[layer_idx](input_tensor=cur_layer_input[:, t, :, :, :], + cur_state=[h, c]) + output_inner.append(h) + + layer_output = torch.stack(output_inner, dim=1) + cur_layer_input = layer_output + + layer_output_list.append(layer_output) + last_state_list.append([h, c]) + + if not self.return_all_layers: + layer_output_list = layer_output_list[-1:] + last_state_list = last_state_list[-1:] + + return layer_output_list, last_state_list + + def _init_hidden(self, batch_size, image_size): + init_states = [] + for i in range(self.num_layers): + init_states.append(self.cell_list[i].init_hidden(batch_size, image_size)) + return init_states + + @staticmethod + def _check_kernel_size_consistency(kernel_size): + if not (isinstance(kernel_size, tuple) or + (isinstance(kernel_size, list) and all([isinstance(elem, tuple) for elem in kernel_size]))): + raise ValueError('`kernel_size` must be tuple or list of tuples') + + @staticmethod + def _extend_for_multilayer(param, num_layers): + if not isinstance(param, list): + param = [param] * num_layers + return param \ No newline at end of file diff --git a/behavior_metrics/brains/gazebo/f1/torch_utils/deepest_lstm_tinypilotnet.py b/behavior_metrics/brains/gazebo/f1/torch_utils/deepest_lstm_tinypilotnet.py new file mode 100644 index 00000000..4affa175 --- /dev/null +++ b/behavior_metrics/brains/gazebo/f1/torch_utils/deepest_lstm_tinypilotnet.py @@ -0,0 +1,45 @@ +import torch +import torch.nn as nn +from .convlstm import ConvLSTM + +class DeepestLSTMTinyPilotNet(nn.Module): + def __init__(self, image_shape, num_labels): + super(DeepestLSTMTinyPilotNet, self).__init__() + self.num_channels = image_shape[2] + self.cn_1 = nn.Conv2d(self.num_channels, 8, kernel_size=3, stride=2) + self.relu_1 = nn.ReLU() + self.cn_2 = nn.Conv2d(8, 8, kernel_size=3, stride=2) + self.relu_2 = nn.ReLU() + self.cn_3 = nn.Conv2d(8, 8, kernel_size=3, stride=2) + self.relu_3 = nn.ReLU() + self.dropout_1 = nn.Dropout(0.2) + + self.clstm_n = ConvLSTM(8, 8, (5, 5), 3, batch_first=True, bias=True, return_all_layers=False) + + self.fc_1 = nn.Linear(8*11*5, 50) + self.relu_fc_1 = nn.ReLU() + self.fc_2 = nn.Linear(50, 10) + self.relu_fc_2 = nn.ReLU() + self.fc_3 = nn.Linear(10, num_labels) + + def forward(self, img): + out = self.cn_1(img) + out = self.relu_1(out) + out = self.cn_2(out) + out = self.relu_2(out) + out = self.cn_3(out) + out = self.relu_3(out) + out = self.dropout_1(out) + # add additional dimension at 1 + out = out.unsqueeze(1) + + _, last_states = self.clstm_n(out) + out = last_states[0][0] # 0 for layer index, 0 for h index + # flatten + out = out.reshape(out.size(0), -1) + out = self.fc_1(out) + out = self.relu_fc_1(out) + out = self.fc_2(out) + out = self.relu_fc_2(out) + out = self.fc_3(out) + return out diff --git a/behavior_metrics/brains/gazebo/f1/torch_utils/pilotnet.py b/behavior_metrics/brains/gazebo/f1/torch_utils/pilotnet.py new file mode 100644 index 00000000..153928ae --- /dev/null +++ b/behavior_metrics/brains/gazebo/f1/torch_utils/pilotnet.py @@ -0,0 +1,58 @@ +import torch +import torch.nn as nn + + +class PilotNet(nn.Module): + def __init__(self, + image_shape, + num_labels): + super(PilotNet, self).__init__() + + self.img_height = image_shape[0] + self.img_width = image_shape[1] + self.num_channels = image_shape[2] + + self.output_size = num_labels + + self.ln_1 = nn.BatchNorm2d(self.num_channels, eps=1e-03) + + self.cn_1 = nn.Conv2d(self.num_channels, 24, kernel_size=5, stride=2) + self.cn_2 = nn.Conv2d(24, 36, kernel_size=5, stride=2) + self.cn_3 = nn.Conv2d(36, 48, kernel_size=5, stride=2) + self.cn_4 = nn.Conv2d(48, 64, kernel_size=3, stride=1) + self.cn_5 = nn.Conv2d(64, 64, kernel_size=3, stride=1) + + self.fc_1 = nn.Linear(1 * 18 * 64, 1164) + self.fc_2 = nn.Linear(1164, 100) + self.fc_3 = nn.Linear(100, 50) + self.fc_4 = nn.Linear(50, 10) + self.fc_5 = nn.Linear(10, self.output_size) + + def forward(self, img): + + out = self.ln_1(img) + + out = self.cn_1(out) + out = torch.relu(out) + out = self.cn_2(out) + out = torch.relu(out) + out = self.cn_3(out) + out = torch.relu(out) + out = self.cn_4(out) + out = torch.relu(out) + out = self.cn_5(out) + out = torch.relu(out) + + out = out.reshape(out.size(0), -1) + + out = self.fc_1(out) + out = torch.relu(out) + out = self.fc_2(out) + out = torch.relu(out) + out = self.fc_3(out) + out = torch.relu(out) + out = self.fc_4(out) + out = torch.relu(out) + out = self.fc_5(out) + + return out diff --git a/behavior_metrics/brains/gazebo/f1/torch_utils/pilotnetStacked.py b/behavior_metrics/brains/gazebo/f1/torch_utils/pilotnetStacked.py new file mode 100644 index 00000000..6d72e6bf --- /dev/null +++ b/behavior_metrics/brains/gazebo/f1/torch_utils/pilotnetStacked.py @@ -0,0 +1,59 @@ +import torch +import torch.nn as nn + + +class PilotNet(nn.Module): + def __init__(self, + image_shape, + num_labels, + horizon): + super(PilotNet, self).__init__() + + self.img_height = image_shape[0] + self.img_width = image_shape[1] + self.num_channels = horizon * image_shape[2] + + self.output_size = num_labels + + self.ln_1 = nn.BatchNorm2d(self.num_channels, eps=1e-03) + + self.cn_1 = nn.Conv2d(self.num_channels, 36, kernel_size=5, stride=2) + self.cn_2 = nn.Conv2d(36, 48, kernel_size=5, stride=2) + self.cn_3 = nn.Conv2d(48, 64, kernel_size=5, stride=2) + self.cn_4 = nn.Conv2d(64, 80, kernel_size=3, stride=1) + self.cn_5 = nn.Conv2d(80, 80, kernel_size=3, stride=1) + + self.fc_1 = nn.Linear(1 * 18 * 80, 1164) + self.fc_2 = nn.Linear(1164, 100) + self.fc_3 = nn.Linear(100, 50) + self.fc_4 = nn.Linear(50, 10) + self.fc_5 = nn.Linear(10, self.output_size) + + def forward(self, img): + + out = self.ln_1(img) + + out = self.cn_1(out) + out = torch.relu(out) + out = self.cn_2(out) + out = torch.relu(out) + out = self.cn_3(out) + out = torch.relu(out) + out = self.cn_4(out) + out = torch.relu(out) + out = self.cn_5(out) + out = torch.relu(out) + + out = out.reshape(out.size(0), -1) + + out = self.fc_1(out) + out = torch.relu(out) + out = self.fc_2(out) + out = torch.relu(out) + out = self.fc_3(out) + out = torch.relu(out) + out = self.fc_4(out) + out = torch.relu(out) + out = self.fc_5(out) + + return out \ No newline at end of file diff --git a/behavior_metrics/brains/f1rl/utils/__init__.py b/behavior_metrics/brains/gazebo/f1rl/__init__.py similarity index 100% rename from behavior_metrics/brains/f1rl/utils/__init__.py rename to behavior_metrics/brains/gazebo/f1rl/__init__.py diff --git a/behavior_metrics/brains/f1rl/brain_f1_dummy.py b/behavior_metrics/brains/gazebo/f1rl/brain_f1_dummy.py similarity index 100% rename from behavior_metrics/brains/f1rl/brain_f1_dummy.py rename to behavior_metrics/brains/gazebo/f1rl/brain_f1_dummy.py diff --git a/behavior_metrics/brains/f1rl/f1_follow_line_camera_dqn.py b/behavior_metrics/brains/gazebo/f1rl/f1_follow_line_camera_dqn.py similarity index 98% rename from behavior_metrics/brains/f1rl/f1_follow_line_camera_dqn.py rename to behavior_metrics/brains/gazebo/f1rl/f1_follow_line_camera_dqn.py index 1d7c9ae6..0482698b 100755 --- a/behavior_metrics/brains/f1rl/f1_follow_line_camera_dqn.py +++ b/behavior_metrics/brains/gazebo/f1rl/f1_follow_line_camera_dqn.py @@ -17,8 +17,8 @@ from gym import logger, wrappers from keras import backend as K -from brains.f1rl.utils.settings import my_board -from brains.f1rl.utils.dqn import DeepQ +from brains.gazebo.f1rl.utils.settings import my_board +from brains.gazebo.f1rl.utils.dqn import DeepQ # To equal the inputs, we set the channels first and the image next. diff --git a/behavior_metrics/brains/f1rl/f1_follow_line_qlearn.py b/behavior_metrics/brains/gazebo/f1rl/f1_follow_line_qlearn.py similarity index 96% rename from behavior_metrics/brains/f1rl/f1_follow_line_qlearn.py rename to behavior_metrics/brains/gazebo/f1rl/f1_follow_line_qlearn.py index 3549ecc0..88cecf62 100755 --- a/behavior_metrics/brains/f1rl/f1_follow_line_qlearn.py +++ b/behavior_metrics/brains/gazebo/f1rl/f1_follow_line_qlearn.py @@ -3,14 +3,14 @@ import pickle import gym -from brains.f1rl.utils import liveplot +from brains.gazebo.f1rl.utils import liveplot import gym_gazebo import numpy as np from gym import logger, wrappers -from brains.f1rl.utils.qlearn import QLearn +from brains.gazebo.f1rl.utils.qlearn import QLearn -import brains.f1rl.utils.settings as settings -from brains.f1rl.utils.settings import actions_set +import brains.gazebo.f1rl.utils.settings as settings +from brains.gazebo.f1rl.utils.settings import actions_set def render(): diff --git a/behavior_metrics/brains/f1rl/f1_follow_line_qlearn_laser.py b/behavior_metrics/brains/gazebo/f1rl/f1_follow_line_qlearn_laser.py similarity index 97% rename from behavior_metrics/brains/f1rl/f1_follow_line_qlearn_laser.py rename to behavior_metrics/brains/gazebo/f1rl/f1_follow_line_qlearn_laser.py index e87a3a9d..276737e4 100755 --- a/behavior_metrics/brains/f1rl/f1_follow_line_qlearn_laser.py +++ b/behavior_metrics/brains/gazebo/f1rl/f1_follow_line_qlearn_laser.py @@ -6,10 +6,10 @@ import numpy as np from gym import logger, wrappers -import brains.f1rl.utils.settings as settings -from brains.f1rl.utils.qlearn import QLearn -from brains.f1rl.utils.settings import actions_set -from brains.f1rl.utils import liveplot +import brains.gazebo.f1rl.utils.settings as settings +from brains.gazebo.f1rl.utils.qlearn import QLearn +from brains.gazebo.f1rl.utils.settings import actions_set +from brains.gazebo.f1rl.utils import liveplot class Brain: """Specific brain for the f1 robot with q learning.""" diff --git a/behavior_metrics/brains/f1rl/train.py b/behavior_metrics/brains/gazebo/f1rl/train.py similarity index 95% rename from behavior_metrics/brains/f1rl/train.py rename to behavior_metrics/brains/gazebo/f1rl/train.py index 85ada9b4..17e2ed16 100755 --- a/behavior_metrics/brains/f1rl/train.py +++ b/behavior_metrics/brains/gazebo/f1rl/train.py @@ -2,13 +2,13 @@ from datetime import datetime import pickle import gym -from brains.f1rl.utils import liveplot +from brains.gazebo.f1rl.utils import liveplot import gym_gazebo import numpy as np from gym import logger, wrappers -from brains.f1rl.utils.qlearn import QLearn -import brains.f1rl.utils.settings as settings -from brains.f1rl.utils.settings import actions_set +from brains.gazebo.f1rl.utils.qlearn import QLearn +import brains.gazebo.f1rl.utils.settings as settings +from brains.gazebo.f1rl.utils.settings import actions_set def render(): diff --git a/behavior_metrics/brains/turtlebot/__init__.py b/behavior_metrics/brains/gazebo/f1rl/utils/__init__.py similarity index 100% rename from behavior_metrics/brains/turtlebot/__init__.py rename to behavior_metrics/brains/gazebo/f1rl/utils/__init__.py diff --git a/behavior_metrics/brains/f1rl/utils/dqn.py b/behavior_metrics/brains/gazebo/f1rl/utils/dqn.py similarity index 100% rename from behavior_metrics/brains/f1rl/utils/dqn.py rename to behavior_metrics/brains/gazebo/f1rl/utils/dqn.py diff --git a/behavior_metrics/brains/f1rl/utils/liveplot.py b/behavior_metrics/brains/gazebo/f1rl/utils/liveplot.py similarity index 100% rename from behavior_metrics/brains/f1rl/utils/liveplot.py rename to behavior_metrics/brains/gazebo/f1rl/utils/liveplot.py diff --git a/behavior_metrics/brains/f1rl/utils/memory.py b/behavior_metrics/brains/gazebo/f1rl/utils/memory.py similarity index 100% rename from behavior_metrics/brains/f1rl/utils/memory.py rename to behavior_metrics/brains/gazebo/f1rl/utils/memory.py diff --git a/behavior_metrics/brains/f1rl/utils/qlearn.py b/behavior_metrics/brains/gazebo/f1rl/utils/qlearn.py similarity index 100% rename from behavior_metrics/brains/f1rl/utils/qlearn.py rename to behavior_metrics/brains/gazebo/f1rl/utils/qlearn.py diff --git a/behavior_metrics/brains/f1rl/utils/ros_gazebo_pose.py b/behavior_metrics/brains/gazebo/f1rl/utils/ros_gazebo_pose.py similarity index 100% rename from behavior_metrics/brains/f1rl/utils/ros_gazebo_pose.py rename to behavior_metrics/brains/gazebo/f1rl/utils/ros_gazebo_pose.py diff --git a/behavior_metrics/brains/f1rl/utils/settings.py b/behavior_metrics/brains/gazebo/f1rl/utils/settings.py similarity index 100% rename from behavior_metrics/brains/f1rl/utils/settings.py rename to behavior_metrics/brains/gazebo/f1rl/utils/settings.py diff --git a/behavior_metrics/models/tf_models/tf_models.txt b/behavior_metrics/brains/gazebo/turtlebot/__init__.py similarity index 100% rename from behavior_metrics/models/tf_models/tf_models.txt rename to behavior_metrics/brains/gazebo/turtlebot/__init__.py diff --git a/behavior_metrics/brains/turtlebot/brain_turtlebot_opencv2.py b/behavior_metrics/brains/gazebo/turtlebot/brain_turtlebot_opencv2.py similarity index 100% rename from behavior_metrics/brains/turtlebot/brain_turtlebot_opencv2.py rename to behavior_metrics/brains/gazebo/turtlebot/brain_turtlebot_opencv2.py diff --git a/behavior_metrics/carla-birdeye-view b/behavior_metrics/carla-birdeye-view new file mode 160000 index 00000000..9f4255cd --- /dev/null +++ b/behavior_metrics/carla-birdeye-view @@ -0,0 +1 @@ +Subproject commit 9f4255cd96c8241d5849ea2bcb52b8b3e5504e52 diff --git a/behavior_metrics/configs/CARLA_launch_files/single_ad_npc_waypoint_publisher.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/single_ad_npc_waypoint_publisher.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/single_ad_npc_waypoint_publisher.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/single_ad_npc_waypoint_publisher.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise.launch similarity index 97% rename from behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise.launch index 47aba9f9..01ca1e1e 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise.launch +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise.launch @@ -10,7 +10,7 @@ - + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_parked_bike.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_bike.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_parked_bike.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_bike.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_parked_bike_car.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_bike_car.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_parked_bike_car.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_bike_car.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_parked_vehicle.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_vehicle.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_parked_vehicle.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_vehicle.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_pedestrian.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_pedestrian.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_pedestrian.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_pedestrian.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_pedestrian_parked_bike_car.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_pedestrian_parked_bike_car.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_pedestrian_parked_bike_car.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_pedestrian_parked_bike_car.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_single_ad_npc.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_single_ad_npc.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_01_anticlockwise_single_ad_npc.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_anticlockwise_single_ad_npc.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_clockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_clockwise.launch similarity index 96% rename from behavior_metrics/configs/CARLA_launch_files/town_01_clockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_clockwise.launch index ea50d689..b4656122 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_01_clockwise.launch +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_clockwise.launch @@ -10,7 +10,7 @@ - + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_01_clockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_clockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_01_clockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_01_clockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_low.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch similarity index 93% rename from behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_low.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch index 30b69148..d9823d00 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_low.launch +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch @@ -52,9 +52,6 @@ - - - @@ -67,7 +64,7 @@ - + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_no_gui.launch similarity index 92% rename from behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_no_gui.launch index 867ad933..d0880035 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_no_gui.launch +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_no_gui.launch @@ -9,7 +9,8 @@ - + + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_clockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_clockwise.launch similarity index 92% rename from behavior_metrics/configs/CARLA_launch_files/town_02_clockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_clockwise.launch index cc7c08d5..87111085 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_02_clockwise.launch +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_clockwise.launch @@ -9,7 +9,8 @@ - + + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_clockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_clockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_02_clockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_clockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_03_anticlockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_03_anticlockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_03_anticlockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_03_anticlockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_03_anticlockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_03_anticlockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_03_anticlockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_03_anticlockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_03_clockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_03_clockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_03_clockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_03_clockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_03_clockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_03_clockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_03_clockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_03_clockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_04_anticlockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_04_anticlockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_04_anticlockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_04_anticlockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_04_anticlockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_04_anticlockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_04_anticlockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_04_anticlockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_04_clockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_04_clockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_04_clockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_04_clockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_04_clockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_04_clockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_04_clockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_04_clockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_05_anticlockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_05_anticlockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_05_anticlockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_05_anticlockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_05_anticlockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_05_anticlockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_05_anticlockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_05_anticlockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_05_clockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_05_clockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_05_clockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_05_clockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_05_clockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_05_clockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_05_clockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_05_clockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_06_anticlockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_06_anticlockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_06_anticlockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_06_anticlockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_06_anticlockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_06_anticlockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_06_anticlockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_06_anticlockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_06_clockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_06_clockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_06_clockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_06_clockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_06_clockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_06_clockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_06_clockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_06_clockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_07_anticlockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_07_anticlockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_07_anticlockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_07_anticlockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_07_anticlockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_07_anticlockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_07_anticlockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_07_anticlockwise_no_gui.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_07_clockwise.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_07_clockwise.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_07_clockwise.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_07_clockwise.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_07_clockwise_no_gui.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_07_clockwise_no_gui.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_07_clockwise_no_gui.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_07_clockwise_no_gui.launch diff --git a/behavior_metrics/configs/default_carla.yml b/behavior_metrics/configs/CARLA/default_carla.yml similarity index 83% rename from behavior_metrics/configs/default_carla.yml rename to behavior_metrics/configs/CARLA/default_carla.yml index 670e59ec..ddc3427c 100644 --- a/behavior_metrics/configs/default_carla.yml +++ b/behavior_metrics/configs/CARLA/default_carla.yml @@ -33,21 +33,21 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning.py' - PilotTimeCycle: 50 - AsyncMode: False + BrainPath: 'brains/CARLA/brain_carla_slow_and_turn.py' + PilotTimeCycle: 50 # Turn up to reduce number of control decisions + AsyncMode: True # Set to False to control simulator time Parameters: - Model: '20230125-120238_pilotnet_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_both_directions_all_towns_adam_AFFINE_PAPER.h5' + Model: '' ImageCropped: True - ImageSize: [ 100,50 ] + ImageSize: [ 200,66 ] ImageNormalized: True PredictionsNormalized: True GPU: True - UseOptimized: True + UseOptimized: False ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise.launch + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/default_carla_tf_lite.yml b/behavior_metrics/configs/CARLA/default_carla_autopilot.yml similarity index 88% rename from behavior_metrics/configs/default_carla_tf_lite.yml rename to behavior_metrics/configs/CARLA/default_carla_autopilot.yml index 911595ef..2eeeb996 100644 --- a/behavior_metrics/configs/default_carla_tf_lite.yml +++ b/behavior_metrics/configs/CARLA/default_carla_autopilot.yml @@ -33,11 +33,10 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning_tf_lite.py' - PilotTimeCycle: 1 - AsyncMode: False + + BrainPath: 'brains/CARLA/brain_carla_autopilot.py' + PilotTimeCycle: 300 Parameters: - Model: 'optimized_pilotnet_models/pilotnet_dynamic_quant.tflite' ImageCropped: True ImageSize: [ 100,50 ] ImageNormalized: True @@ -46,9 +45,9 @@ Behaviors: UseOptimized: True ImageTranform: '' Type: 'CARLA' - Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise.launch RandomSpawnPoint: False + Simulation: + World: configs/CARLA/CARLA_launch_files/town_01_anticlockwise.launch Dataset: In: '/tmp/my_bag.bag' Out: '' diff --git a/behavior_metrics/configs/default_carla_multiple.yml b/behavior_metrics/configs/CARLA/default_carla_multiple.yml similarity index 62% rename from behavior_metrics/configs/default_carla_multiple.yml rename to behavior_metrics/configs/CARLA/default_carla_multiple.yml index 69de86e1..94a761f4 100644 --- a/behavior_metrics/configs/default_carla_multiple.yml +++ b/behavior_metrics/configs/CARLA/default_carla_multiple.yml @@ -35,40 +35,22 @@ Behaviors: MaxW: 0.3 BrainPath: [ - 'brains/CARLA/brain_carla_bird_eye_deep_learning.py', - 'brains/CARLA/brain_carla_bird_eye_deep_learning.py', - - 'brains/CARLA/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py', - 'brains/CARLA/brain_carla_bird_eye_deep_learning_x3_t_t-4_t-9.py', - - 'brains/CARLA/brain_carla_bird_eye_deep_learning_previous_v.py', - 'brains/CARLA/brain_carla_bird_eye_deep_learning_previous_v.py', - - 'brains/CARLA/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py', - 'brains/CARLA/brain_carla_bird_eye_deep_learning_x3_previous_v_t_t-4_t-9.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py', + 'brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch.py', ] - PilotTimeCycle: 100 - AsyncMode: False + PilotTimeCycle: 50 + AsyncMode: True Parameters: Model: [ - '20230125-120238_pilotnet_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_both_directions_all_towns_adam_AFFINE_PAPER.h5', - '20230126-183457_deepestLSTMTinyPilotNet_CARLA_14_12_dataset_bird_eye_400_epochs_no_flip_3_output_both_directions_all_towns__less_learning_rate_PAPER_cp.h5', - - '20230220-105422_pilotnet_small_more_more_LSTM_x3_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_both_directions_all_towns_sequences_more_more_extreme_t_5_t_10_dataset_AFFINE_PAPER_cp.h5', - '20230222-110851_memDCCP_small_LSTM_2_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_both_directions_all_towns_sequences_more_more_extreme_AFFINE_PAPER_cp.h5', - - '20230127-180655_pilotnet_CARLA_17_10_dataset_bird_eye_300_epochs_no_flip_3_output_velocity_all_towns_vel_30_AFFINE.h5', - '20230127-180856_deepestLSTMTinyPilotNet_CARLA_17_10_dataset_bird_eye_300_epochs_no_flip_3_output_velocity_all_towns_vel_30_AFFINE_PAPER.h5', - - '20230221-162112_pilotnet_x3_small_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_velocity_both_directions_all_towns_sequences_more_extreme_previous_V_AFFINE_PAPER_cp.h5', - '20230221-175351_memDCCP_small_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_velocity_both_directions_all_towns_sequences_more_extreme_previous_V_AFFINE_PAPER_cp.h5' + 'pilotnet.h5', + 'pilotnet_model.pth' ] ImageCropped: True ImageSize: [ 100,50 ] ImageNormalized: True PredictionsNormalized: True GPU: True - UseOptimized: True + UseOptimized: False ImageTranform: '' Type: 'CARLA' Experiment: @@ -79,15 +61,15 @@ Behaviors: Repetitions: 5 Simulation: World: [ - configs/CARLA_launch_files/town_01_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_02_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_03_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_04_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_05_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_06_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_07_anticlockwise_no_gui.launch + configs/CARLA/CARLA_launch_files/town_01_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_02_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_03_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_04_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_05_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_06_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_07_anticlockwise_no_gui.launch ] - RandomSpawnPoint: True + RandomSpawnPoint: False SpawnPoints: [ [ "10.0, 2.0, 1.37, 0.0, 0.0, 180.0", diff --git a/behavior_metrics/configs/default_carla_multiple_simple.yml b/behavior_metrics/configs/CARLA/default_carla_multiple_simple.yml similarity index 77% rename from behavior_metrics/configs/default_carla_multiple_simple.yml rename to behavior_metrics/configs/CARLA/default_carla_multiple_simple.yml index 3daed2e5..9891f9ec 100644 --- a/behavior_metrics/configs/default_carla_multiple_simple.yml +++ b/behavior_metrics/configs/CARLA/default_carla_multiple_simple.yml @@ -31,7 +31,7 @@ Behaviors: MaxW: 0.3 BrainPath: [ - 'brains/CARLA/brain_carla_bird_eye_deep_learning.py' + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' ] PilotTimeCycle: 100 Parameters: @@ -57,17 +57,17 @@ Behaviors: World: [ - configs/CARLA_launch_files/town_04_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_04_clockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_04_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_04_clockwise_no_gui.launch, - configs/CARLA_launch_files/town_05_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_05_clockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_05_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_05_clockwise_no_gui.launch, - configs/CARLA_launch_files/town_06_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_06_clockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_06_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_06_clockwise_no_gui.launch, - configs/CARLA_launch_files/town_07_anticlockwise_no_gui.launch, - configs/CARLA_launch_files/town_07_clockwise_no_gui.launch + configs/CARLA/CARLA_launch_files/town_07_anticlockwise_no_gui.launch, + configs/CARLA/CARLA_launch_files/town_07_clockwise_no_gui.launch ] Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/CARLA/default_carla_multiple_tensorflow_optimizations.yml b/behavior_metrics/configs/CARLA/default_carla_multiple_tensorflow_optimizations.yml new file mode 100644 index 00000000..1c38024b --- /dev/null +++ b/behavior_metrics/configs/CARLA/default_carla_multiple_tensorflow_optimizations.yml @@ -0,0 +1,120 @@ +Behaviors: + Robot: + Sensors: + Cameras: + Camera_0: + Name: 'camera_0' + Topic: '/carla/ego_vehicle/rgb_front/image' + Camera_1: + Name: 'camera_1' + Topic: '/carla/ego_vehicle/rgb_view/image' + Camera_2: + Name: 'camera_2' + Topic: '/carla/ego_vehicle/semantic_segmentation_front/image' + Camera_3: + Name: 'camera_3' + Topic: '/carla/ego_vehicle/dvs_front/image' + Pose3D: + Pose3D_0: + Name: 'pose3d_0' + Topic: '/carla/ego_vehicle/odometry' + BirdEyeView: + BirdEyeView_0: + Name: 'bird_eye_view_0' + Topic: '' + Speedometer: + Speedometer_0: + Name: 'speedometer_0' + Topic: '/carla/ego_vehicle/speedometer' + Actuators: + CARLA_Motors: + Motors_0: + Name: 'motors_0' + Topic: '/carla/ego_vehicle/vehicle_control_cmd' + MaxV: 3 + MaxW: 0.3 + + BrainPath: [ + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py', + + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tf_lite.py', + ] + PilotTimeCycle: 50 + AsyncMode: True + Parameters: + Model: [ + 'pilotnet.h5', + + 'optimized_pilotnet_models_tensorflow/pilotnet_model.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_dynamic_quant.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_int_quant.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_intflt_quant.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_float16_quant.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_quant_aware.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_pruned.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_pruned_quan.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_cqat_model.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_pqat_model.tflite', + 'optimized_pilotnet_models_tensorflow/pilotnet_pcqat_model.tflite' + ] + ImageCropped: True + ImageSize: [ 100,50 ] + ImageNormalized: True + PredictionsNormalized: True + GPU: True + UseOptimized: True + ImageTranform: '' + Type: 'CARLA' + Experiment: + Name: "Experiment name" + Description: "Experiment description" + UseWorldTimeouts: True + Timeout: [10] # for each world! + Repetitions: 5 + Simulation: + World: [ + configs/CARLA/CARLA_launch_files/town_02_anticlockwise_no_gui.launch, + ] + RandomSpawnPoint: False + SpawnPoints: [ + [ + "-7.0, -270.6, 1.37, 0.0, 0.0, -90.0", + "-7.0, -270.6, 1.37, 0.0, 0.0, -90.0", + "-7.0, -270.6, 1.37, 0.0, 0.0, -90.0", + "-7.0, -270.6, 1.37, 0.0, 0.0, -90.0", + "-7.0, -270.6, 1.37, 0.0, 0.0, -90.0" + ] + ] + Dataset: + In: '/tmp/my_bag.bag' + Out: '' + Stats: + Out: './' + PerfectLap: './perfect_bags/lap-simple-circuit.bag' + Layout: + Frame_0: + Name: frame_0 + Geometry: [1, 1, 1, 1] + Data: rgbimage + Frame_1: + Name: frame_1 + Geometry: [0, 1, 1, 1] + Data: rgbimage + Frame_2: + Name: frame_2 + Geometry: [0, 2, 1, 1] + Data: rgbimage + Frame_3: + Name: frame_3 + Geometry: [1, 2, 1, 1] + Data: rgbimage diff --git a/behavior_metrics/configs/default_carla_parked_bike.yml b/behavior_metrics/configs/CARLA/default_carla_parked_bike.yml similarity index 93% rename from behavior_metrics/configs/default_carla_parked_bike.yml rename to behavior_metrics/configs/CARLA/default_carla_parked_bike.yml index daf30e07..aa72b9aa 100644 --- a/behavior_metrics/configs/default_carla_parked_bike.yml +++ b/behavior_metrics/configs/CARLA/default_carla_parked_bike.yml @@ -33,7 +33,7 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning.py' + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' PilotTimeCycle: 100 AsyncMode: False Parameters: @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise_parked_bike.launch + World: configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_bike.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/default_carla_parked_bike_car.yml b/behavior_metrics/configs/CARLA/default_carla_parked_bike_car.yml similarity index 93% rename from behavior_metrics/configs/default_carla_parked_bike_car.yml rename to behavior_metrics/configs/CARLA/default_carla_parked_bike_car.yml index ebee5b85..e47e48a6 100644 --- a/behavior_metrics/configs/default_carla_parked_bike_car.yml +++ b/behavior_metrics/configs/CARLA/default_carla_parked_bike_car.yml @@ -33,7 +33,7 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning.py' + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' PilotTimeCycle: 100 AsyncMode: False Parameters: @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise_parked_bike_car.launch + World: configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_bike_car.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/default_carla_parked_vehicle.yml b/behavior_metrics/configs/CARLA/default_carla_parked_vehicle.yml similarity index 93% rename from behavior_metrics/configs/default_carla_parked_vehicle.yml rename to behavior_metrics/configs/CARLA/default_carla_parked_vehicle.yml index fce12b36..5808d6a8 100644 --- a/behavior_metrics/configs/default_carla_parked_vehicle.yml +++ b/behavior_metrics/configs/CARLA/default_carla_parked_vehicle.yml @@ -33,7 +33,7 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning.py' + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' PilotTimeCycle: 100 AsyncMode: False Parameters: @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise_parked_vehicle.launch + World: configs/CARLA/CARLA_launch_files/town_01_anticlockwise_parked_vehicle.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/default_carla_pedestrian.yml b/behavior_metrics/configs/CARLA/default_carla_pedestrian.yml similarity index 93% rename from behavior_metrics/configs/default_carla_pedestrian.yml rename to behavior_metrics/configs/CARLA/default_carla_pedestrian.yml index d28137b6..9654c06f 100644 --- a/behavior_metrics/configs/default_carla_pedestrian.yml +++ b/behavior_metrics/configs/CARLA/default_carla_pedestrian.yml @@ -33,7 +33,7 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning.py' + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' PilotTimeCycle: 100 AsyncMode: False Parameters: @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise_pedestrian.launch + World: configs/CARLA/CARLA_launch_files/town_01_anticlockwise_pedestrian.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/default_carla_pedestrian_parked_bike_car.yml b/behavior_metrics/configs/CARLA/default_carla_pedestrian_parked_bike_car.yml similarity index 92% rename from behavior_metrics/configs/default_carla_pedestrian_parked_bike_car.yml rename to behavior_metrics/configs/CARLA/default_carla_pedestrian_parked_bike_car.yml index bc931f8d..54358fad 100644 --- a/behavior_metrics/configs/default_carla_pedestrian_parked_bike_car.yml +++ b/behavior_metrics/configs/CARLA/default_carla_pedestrian_parked_bike_car.yml @@ -33,7 +33,7 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning.py' + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' PilotTimeCycle: 100 AsyncMode: False Parameters: @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise_pedestrian_parked_bike_car.launch + World: configs/CARLA/CARLA_launch_files/town_01_anticlockwise_pedestrian_parked_bike_car.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/default_carla_single_ad_npc.yml b/behavior_metrics/configs/CARLA/default_carla_single_ad_npc.yml similarity index 89% rename from behavior_metrics/configs/default_carla_single_ad_npc.yml rename to behavior_metrics/configs/CARLA/default_carla_single_ad_npc.yml index 57564423..55a9eb48 100644 --- a/behavior_metrics/configs/default_carla_single_ad_npc.yml +++ b/behavior_metrics/configs/CARLA/default_carla_single_ad_npc.yml @@ -33,7 +33,7 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning.py' + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' PilotTimeCycle: 50 AsyncMode: False Parameters: @@ -47,8 +47,8 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise_single_ad_npc.launch - WaypointPublisher: configs/CARLA_launch_files/single_ad_npc_waypoint_publisher.launch + World: configs/CARLA/CARLA_launch_files/town_01_anticlockwise_single_ad_npc.launch + WaypointPublisher: configs/CARLA/CARLA_launch_files/single_ad_npc_waypoint_publisher.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/default_carla_subjective_vision.yml b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml similarity index 95% rename from behavior_metrics/configs/default_carla_subjective_vision.yml rename to behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml index 77365d0d..4d7a01b6 100644 --- a/behavior_metrics/configs/default_carla_subjective_vision.yml +++ b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml @@ -47,9 +47,8 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch RandomSpawnPoint: False - MultiCar: True Dataset: In: '/tmp/my_bag.bag' Out: '' diff --git a/behavior_metrics/configs/default_carla_tensor_rt.yml b/behavior_metrics/configs/CARLA/default_carla_tensor_rt.yml similarity index 88% rename from behavior_metrics/configs/default_carla_tensor_rt.yml rename to behavior_metrics/configs/CARLA/default_carla_tensor_rt.yml index 3b860815..fe6b7102 100644 --- a/behavior_metrics/configs/default_carla_tensor_rt.yml +++ b/behavior_metrics/configs/CARLA/default_carla_tensor_rt.yml @@ -33,13 +33,13 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning_tensor_rt.py' + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning_tensor_rt.py' PilotTimeCycle: 1 AsyncMode: False Parameters: - Model: 'pilotnet_tftrt_int8' + Model: 'optimized_pilotnet_models_tensorflow/pilotnet_tftrt_int8_2' ImageCropped: True - ImageSize: [ 100,50 ] + ImageSize: [ 200,66 ] ImageNormalized: True PredictionsNormalized: True GPU: True @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise.launch + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/CARLA/default_carla_tensorflow.yml b/behavior_metrics/configs/CARLA/default_carla_tensorflow.yml new file mode 100644 index 00000000..46fae066 --- /dev/null +++ b/behavior_metrics/configs/CARLA/default_carla_tensorflow.yml @@ -0,0 +1,74 @@ +Behaviors: + Robot: + Sensors: + Cameras: + Camera_0: + Name: 'camera_0' + Topic: '/carla/ego_vehicle/rgb_front/image' + Camera_1: + Name: 'camera_1' + Topic: '/carla/ego_vehicle/rgb_view/image' + Camera_2: + Name: 'camera_2' + Topic: '/carla/ego_vehicle/semantic_segmentation_front/image' + Camera_3: + Name: 'camera_3' + Topic: '/carla/ego_vehicle/dvs_front/image' + Pose3D: + Pose3D_0: + Name: 'pose3d_0' + Topic: '/carla/ego_vehicle/odometry' + BirdEyeView: + BirdEyeView_0: + Name: 'bird_eye_view_0' + Topic: '' + Speedometer: + Speedometer_0: + Name: 'speedometer_0' + Topic: '/carla/ego_vehicle/speedometer' + Actuators: + CARLA_Motors: + Motors_0: + Name: 'motors_0' + Topic: '/carla/ego_vehicle/vehicle_control_cmd' + MaxV: 3 + MaxW: 0.3 + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' + PilotTimeCycle: 50 # Turn up to reduce number of control decisions + AsyncMode: True # Set to False to control simulator time + Parameters: + Model: 'pilotnet.h5' + ImageCropped: True + ImageSize: [ 200,66 ] + ImageNormalized: True + PredictionsNormalized: True + GPU: True + UseOptimized: False + ImageTranform: '' + Type: 'CARLA' + Simulation: + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise.launch + RandomSpawnPoint: False + Dataset: + In: '/tmp/my_bag.bag' + Out: '' + Stats: + Out: './' + PerfectLap: './perfect_bags/lap-simple-circuit.bag' + Layout: + Frame_0: + Name: frame_0 + Geometry: [1, 1, 1, 1] + Data: rgbimage + Frame_1: + Name: frame_1 + Geometry: [0, 1, 1, 1] + Data: rgbimage + Frame_2: + Name: frame_2 + Geometry: [0, 2, 1, 1] + Data: rgbimage + Frame_3: + Name: frame_3 + Geometry: [1, 2, 1, 1] + Data: rgbimage diff --git a/behavior_metrics/configs/CARLA/default_carla_tf_lite.yml b/behavior_metrics/configs/CARLA/default_carla_tf_lite.yml new file mode 100644 index 00000000..e69de29b diff --git a/behavior_metrics/configs/default_carla_torch.yml b/behavior_metrics/configs/CARLA/default_carla_torch.yml similarity index 89% rename from behavior_metrics/configs/default_carla_torch.yml rename to behavior_metrics/configs/CARLA/default_carla_torch.yml index 3fd0ba6c..6f9865d2 100644 --- a/behavior_metrics/configs/default_carla_torch.yml +++ b/behavior_metrics/configs/CARLA/default_carla_torch.yml @@ -33,11 +33,11 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_bird_eye_deep_learning_torch.py' - PilotTimeCycle: 100 - AsyncMode: False + BrainPath: 'brains/CARLA/pytorch/brain_carla_bird_eye_deep_learning_torch.py' + PilotTimeCycle: 50 + AsyncMode: True Parameters: - Model: 'pilot_net_model_best_17_04_c_3.pth' + Model: 'pilotnet_model.pth' ImageCropped: True ImageSize: [ 100,50 ] ImageNormalized: True @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA_launch_files/town_01_anticlockwise.launch + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise.launch RandomSpawnPoint: False Dataset: In: '/tmp/my_bag.bag' diff --git a/behavior_metrics/configs/CARLA/default_carla_traffic.yml b/behavior_metrics/configs/CARLA/default_carla_traffic.yml new file mode 100644 index 00000000..ebb625ef --- /dev/null +++ b/behavior_metrics/configs/CARLA/default_carla_traffic.yml @@ -0,0 +1,78 @@ +Behaviors: + Robot: + Sensors: + Cameras: + Camera_0: + Name: 'camera_0' + Topic: '/carla/ego_vehicle/rgb_front/image' + Camera_1: + Name: 'camera_1' + Topic: '/carla/ego_vehicle/rgb_view/image' + Camera_2: + Name: 'camera_2' + Topic: '/carla/ego_vehicle/semantic_segmentation_front/image' + Camera_3: + Name: 'camera_3' + Topic: '/carla/ego_vehicle/dvs_front/image' + Pose3D: + Pose3D_0: + Name: 'pose3d_0' + Topic: '/carla/ego_vehicle/odometry' + BirdEyeView: + BirdEyeView_0: + Name: 'bird_eye_view_0' + Topic: '' + Speedometer: + Speedometer_0: + Name: 'speedometer_0' + Topic: '/carla/ego_vehicle/speedometer' + Actuators: + CARLA_Motors: + Motors_0: + Name: 'motors_0' + Topic: '/carla/ego_vehicle/vehicle_control_cmd' + MaxV: 3 + MaxW: 0.3 + BrainPath: 'brains/CARLA/tensorflow/brain_carla_bird_eye_deep_learning.py' + PilotTimeCycle: 50 + AsyncMode: False + Parameters: + Model: '20230126-183457_deepestLSTMTinyPilotNet_CARLA_14_12_dataset_bird_eye_400_epochs_no_flip_3_output_both_directions_all_towns__less_learning_rate_PAPER_cp.h5' + ImageCropped: True + ImageSize: [ 100,50 ] + ImageNormalized: True + PredictionsNormalized: True + GPU: True + UseOptimized: True + ImageTranform: '' + Type: 'CARLA' + Simulation: + World: configs/CARLA/CARLA_launch_files/town_01_anticlockwise.launch + RandomSpawnPoint: False + NumberOfVehicle: 50 + NumberOfWalker: 50 + PercentagePedestriansRunning: 0.5 + PercentagePedestriansCrossing: 0.5 + Dataset: + In: '/tmp/my_bag.bag' + Out: '' + Stats: + Out: './' + PerfectLap: './perfect_bags/lap-simple-circuit.bag' + Layout: + Frame_0: + Name: frame_0 + Geometry: [1, 1, 1, 1] + Data: rgbimage + Frame_1: + Name: frame_1 + Geometry: [0, 1, 1, 1] + Data: rgbimage + Frame_2: + Name: frame_2 + Geometry: [0, 2, 1, 1] + Data: rgbimage + Frame_3: + Name: frame_3 + Geometry: [1, 2, 1, 1] + Data: rgbimage diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/main_car.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/main_car.json deleted file mode 100644 index d687d1c9..00000000 --- a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/main_car.json +++ /dev/null @@ -1,161 +0,0 @@ -{ - "objects": - [ - { - "type": "sensor.pseudo.traffic_lights", - "id": "traffic_lights" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.actor_list", - "id": "actor_list" - }, - { - "type": "sensor.pseudo.markers", - "id": "markers" - }, - { - "type": "sensor.pseudo.opendrive_map", - "id": "map" - }, - { - "type": "vehicle.tesla.model3", - "id": "ego_vehicle", - "sensors": - [ - { - "type": "sensor.camera.rgb", - "id": "rgb_front", - "spawn_point": {"x": 2.5, "y": 0.0, "z": 0.8, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "image_size_x": 640, - "image_size_y": 480 - }, - { - "type": "sensor.camera.rgb", - "id": "rgb_view", - "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0, - "attached_objects": - [ - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "sensor.lidar.ray_cast", - "id": "lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20, - "noise_stddev": 0.0 - }, - { - "type": "sensor.lidar.ray_cast_semantic", - "id": "semantic_lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20 - }, - { - "type": "sensor.other.radar", - "id": "radar_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "horizontal_fov": 30.0, - "vertical_fov": 10.0, - "points_per_second": 1500, - "range": 100.0 - }, - { - "type": "sensor.camera.semantic_segmentation", - "id": "semantic_segmentation_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.depth", - "id": "depth_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.dvs", - "id": "dvs_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70, - "positive_threshold": 0.3, - "negative_threshold": 0.3, - "sigma_positive_threshold": 0.0, - "sigma_negative_threshold": 0.0, - "use_log": true, - "log_eps": 0.001 - }, - { - "type": "sensor.other.gnss", - "id": "gnss", - "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, - "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, - "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 - }, - { - "type": "sensor.other.imu", - "id": "imu", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, - "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, - "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 - }, - { - "type": "sensor.other.collision", - "id": "collision", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.other.lane_invasion", - "id": "lane_invasion", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.pseudo.tf", - "id": "tf" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - }, - { - "type": "sensor.pseudo.speedometer", - "id": "speedometer" - }, - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - } - ] -} diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_bike_car_objects.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_bike_car_objects.json deleted file mode 100644 index 70124e1f..00000000 --- a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_bike_car_objects.json +++ /dev/null @@ -1,170 +0,0 @@ -{ - "objects": - [ - { - "type": "sensor.pseudo.traffic_lights", - "id": "traffic_lights" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.actor_list", - "id": "actor_list" - }, - { - "type": "sensor.pseudo.markers", - "id": "markers" - }, - { - "type": "sensor.pseudo.opendrive_map", - "id": "map" - }, - { - "type": "vehicle.tesla.model3", - "id": "ego_vehicle", - "sensors": - [ - { - "type": "sensor.camera.rgb", - "id": "rgb_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0 - }, - { - "type": "sensor.camera.rgb", - "id": "rgb_view", - "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0, - "attached_objects": - [ - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "sensor.lidar.ray_cast", - "id": "lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20, - "noise_stddev": 0.0 - }, - { - "type": "sensor.lidar.ray_cast_semantic", - "id": "semantic_lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20 - }, - { - "type": "sensor.other.radar", - "id": "radar_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "horizontal_fov": 30.0, - "vertical_fov": 10.0, - "points_per_second": 1500, - "range": 100.0 - }, - { - "type": "sensor.camera.semantic_segmentation", - "id": "semantic_segmentation_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.depth", - "id": "depth_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.dvs", - "id": "dvs_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70, - "positive_threshold": 0.3, - "negative_threshold": 0.3, - "sigma_positive_threshold": 0.0, - "sigma_negative_threshold": 0.0, - "use_log": true, - "log_eps": 0.001 - }, - { - "type": "sensor.other.gnss", - "id": "gnss", - "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, - "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, - "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 - }, - { - "type": "sensor.other.imu", - "id": "imu", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, - "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, - "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 - }, - { - "type": "sensor.other.collision", - "id": "collision", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.other.lane_invasion", - "id": "lane_invasion", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.pseudo.tf", - "id": "tf" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - }, - { - "type": "sensor.pseudo.speedometer", - "id": "speedometer" - }, - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "vehicle.yamaha.yzf", - "id": "parked_bike" - }, - { - "type": "vehicle.audi.a2", - "id": "parked_car" - } - ] -} \ No newline at end of file diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_bike_objects.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_bike_objects.json deleted file mode 100644 index 816ebda5..00000000 --- a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_bike_objects.json +++ /dev/null @@ -1,166 +0,0 @@ -{ - "objects": - [ - { - "type": "sensor.pseudo.traffic_lights", - "id": "traffic_lights" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.actor_list", - "id": "actor_list" - }, - { - "type": "sensor.pseudo.markers", - "id": "markers" - }, - { - "type": "sensor.pseudo.opendrive_map", - "id": "map" - }, - { - "type": "vehicle.tesla.model3", - "id": "ego_vehicle", - "sensors": - [ - { - "type": "sensor.camera.rgb", - "id": "rgb_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0 - }, - { - "type": "sensor.camera.rgb", - "id": "rgb_view", - "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0, - "attached_objects": - [ - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "sensor.lidar.ray_cast", - "id": "lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20, - "noise_stddev": 0.0 - }, - { - "type": "sensor.lidar.ray_cast_semantic", - "id": "semantic_lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20 - }, - { - "type": "sensor.other.radar", - "id": "radar_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "horizontal_fov": 30.0, - "vertical_fov": 10.0, - "points_per_second": 1500, - "range": 100.0 - }, - { - "type": "sensor.camera.semantic_segmentation", - "id": "semantic_segmentation_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.depth", - "id": "depth_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.dvs", - "id": "dvs_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70, - "positive_threshold": 0.3, - "negative_threshold": 0.3, - "sigma_positive_threshold": 0.0, - "sigma_negative_threshold": 0.0, - "use_log": true, - "log_eps": 0.001 - }, - { - "type": "sensor.other.gnss", - "id": "gnss", - "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, - "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, - "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 - }, - { - "type": "sensor.other.imu", - "id": "imu", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, - "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, - "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 - }, - { - "type": "sensor.other.collision", - "id": "collision", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.other.lane_invasion", - "id": "lane_invasion", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.pseudo.tf", - "id": "tf" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - }, - { - "type": "sensor.pseudo.speedometer", - "id": "speedometer" - }, - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "vehicle.yamaha.yzf", - "id": "parked_bike" - } - ] -} \ No newline at end of file diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_car_objects.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_car_objects.json deleted file mode 100644 index 017dfb0e..00000000 --- a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/parked_car_objects.json +++ /dev/null @@ -1,166 +0,0 @@ -{ - "objects": - [ - { - "type": "sensor.pseudo.traffic_lights", - "id": "traffic_lights" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.actor_list", - "id": "actor_list" - }, - { - "type": "sensor.pseudo.markers", - "id": "markers" - }, - { - "type": "sensor.pseudo.opendrive_map", - "id": "map" - }, - { - "type": "vehicle.tesla.model3", - "id": "ego_vehicle", - "sensors": - [ - { - "type": "sensor.camera.rgb", - "id": "rgb_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0 - }, - { - "type": "sensor.camera.rgb", - "id": "rgb_view", - "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0, - "attached_objects": - [ - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "sensor.lidar.ray_cast", - "id": "lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20, - "noise_stddev": 0.0 - }, - { - "type": "sensor.lidar.ray_cast_semantic", - "id": "semantic_lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20 - }, - { - "type": "sensor.other.radar", - "id": "radar_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "horizontal_fov": 30.0, - "vertical_fov": 10.0, - "points_per_second": 1500, - "range": 100.0 - }, - { - "type": "sensor.camera.semantic_segmentation", - "id": "semantic_segmentation_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.depth", - "id": "depth_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.dvs", - "id": "dvs_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70, - "positive_threshold": 0.3, - "negative_threshold": 0.3, - "sigma_positive_threshold": 0.0, - "sigma_negative_threshold": 0.0, - "use_log": true, - "log_eps": 0.001 - }, - { - "type": "sensor.other.gnss", - "id": "gnss", - "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, - "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, - "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 - }, - { - "type": "sensor.other.imu", - "id": "imu", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, - "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, - "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 - }, - { - "type": "sensor.other.collision", - "id": "collision", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.other.lane_invasion", - "id": "lane_invasion", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.pseudo.tf", - "id": "tf" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - }, - { - "type": "sensor.pseudo.speedometer", - "id": "speedometer" - }, - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "vehicle.audi.a2", - "id": "parked_vehicle" - } - ] -} \ No newline at end of file diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/pedestrian_objects.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/pedestrian_objects.json deleted file mode 100644 index 19e2556f..00000000 --- a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/pedestrian_objects.json +++ /dev/null @@ -1,166 +0,0 @@ -{ - "objects": - [ - { - "type": "sensor.pseudo.traffic_lights", - "id": "traffic_lights" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.actor_list", - "id": "actor_list" - }, - { - "type": "sensor.pseudo.markers", - "id": "markers" - }, - { - "type": "sensor.pseudo.opendrive_map", - "id": "map" - }, - { - "type": "vehicle.tesla.model3", - "id": "ego_vehicle", - "sensors": - [ - { - "type": "sensor.camera.rgb", - "id": "rgb_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0 - }, - { - "type": "sensor.camera.rgb", - "id": "rgb_view", - "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0, - "attached_objects": - [ - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "sensor.lidar.ray_cast", - "id": "lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20, - "noise_stddev": 0.0 - }, - { - "type": "sensor.lidar.ray_cast_semantic", - "id": "semantic_lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20 - }, - { - "type": "sensor.other.radar", - "id": "radar_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "horizontal_fov": 30.0, - "vertical_fov": 10.0, - "points_per_second": 1500, - "range": 100.0 - }, - { - "type": "sensor.camera.semantic_segmentation", - "id": "semantic_segmentation_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.depth", - "id": "depth_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.dvs", - "id": "dvs_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70, - "positive_threshold": 0.3, - "negative_threshold": 0.3, - "sigma_positive_threshold": 0.0, - "sigma_negative_threshold": 0.0, - "use_log": true, - "log_eps": 0.001 - }, - { - "type": "sensor.other.gnss", - "id": "gnss", - "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, - "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, - "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 - }, - { - "type": "sensor.other.imu", - "id": "imu", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, - "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, - "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 - }, - { - "type": "sensor.other.collision", - "id": "collision", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.other.lane_invasion", - "id": "lane_invasion", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.pseudo.tf", - "id": "tf" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - }, - { - "type": "sensor.pseudo.speedometer", - "id": "speedometer" - }, - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "walker.pedestrian.0001", - "id": "pedestrian" - } - ] -} \ No newline at end of file diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/pedestrian_parked_bike_car_objects.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/pedestrian_parked_bike_car_objects.json deleted file mode 100644 index f4079106..00000000 --- a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/pedestrian_parked_bike_car_objects.json +++ /dev/null @@ -1,174 +0,0 @@ -{ - "objects": - [ - { - "type": "sensor.pseudo.traffic_lights", - "id": "traffic_lights" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.actor_list", - "id": "actor_list" - }, - { - "type": "sensor.pseudo.markers", - "id": "markers" - }, - { - "type": "sensor.pseudo.opendrive_map", - "id": "map" - }, - { - "type": "vehicle.tesla.model3", - "id": "ego_vehicle", - "sensors": - [ - { - "type": "sensor.camera.rgb", - "id": "rgb_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0 - }, - { - "type": "sensor.camera.rgb", - "id": "rgb_view", - "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0, - "attached_objects": - [ - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "sensor.lidar.ray_cast", - "id": "lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20, - "noise_stddev": 0.0 - }, - { - "type": "sensor.lidar.ray_cast_semantic", - "id": "semantic_lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20 - }, - { - "type": "sensor.other.radar", - "id": "radar_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "horizontal_fov": 30.0, - "vertical_fov": 10.0, - "points_per_second": 1500, - "range": 100.0 - }, - { - "type": "sensor.camera.semantic_segmentation", - "id": "semantic_segmentation_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.depth", - "id": "depth_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.dvs", - "id": "dvs_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70, - "positive_threshold": 0.3, - "negative_threshold": 0.3, - "sigma_positive_threshold": 0.0, - "sigma_negative_threshold": 0.0, - "use_log": true, - "log_eps": 0.001 - }, - { - "type": "sensor.other.gnss", - "id": "gnss", - "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, - "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, - "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 - }, - { - "type": "sensor.other.imu", - "id": "imu", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, - "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, - "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 - }, - { - "type": "sensor.other.collision", - "id": "collision", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.other.lane_invasion", - "id": "lane_invasion", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.pseudo.tf", - "id": "tf" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - }, - { - "type": "sensor.pseudo.speedometer", - "id": "speedometer" - }, - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "vehicle.yamaha.yzf", - "id": "parked_bike" - }, - { - "type": "vehicle.audi.a2", - "id": "parked_car" - }, - { - "type": "walker.pedestrian.0001", - "id": "pedestrian" - } - ] -} \ No newline at end of file diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car.json deleted file mode 100644 index 46758eb4..00000000 --- a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car.json +++ /dev/null @@ -1,178 +0,0 @@ -{ - "objects": - [ - { - "type": "sensor.pseudo.traffic_lights", - "id": "traffic_lights" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.actor_list", - "id": "actor_list" - }, - { - "type": "sensor.pseudo.markers", - "id": "markers" - }, - { - "type": "sensor.pseudo.opendrive_map", - "id": "map" - }, - { - "type": "vehicle.tesla.model3", - "id": "ego_vehicle", - "sensors": - [ - { - "type": "sensor.camera.rgb", - "id": "rgb_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0 - }, - { - "type": "sensor.camera.rgb", - "id": "rgb_view", - "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0, - "attached_objects": - [ - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "sensor.lidar.ray_cast", - "id": "lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20, - "noise_stddev": 0.0 - }, - { - "type": "sensor.lidar.ray_cast_semantic", - "id": "semantic_lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20 - }, - { - "type": "sensor.other.radar", - "id": "radar_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "horizontal_fov": 30.0, - "vertical_fov": 10.0, - "points_per_second": 1500, - "range": 100.0 - }, - { - "type": "sensor.camera.semantic_segmentation", - "id": "semantic_segmentation_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.depth", - "id": "depth_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.dvs", - "id": "dvs_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70, - "positive_threshold": 0.3, - "negative_threshold": 0.3, - "sigma_positive_threshold": 0.0, - "sigma_negative_threshold": 0.0, - "use_log": true, - "log_eps": 0.001 - }, - { - "type": "sensor.other.gnss", - "id": "gnss", - "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, - "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, - "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 - }, - { - "type": "sensor.other.imu", - "id": "imu", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, - "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, - "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 - }, - { - "type": "sensor.other.collision", - "id": "collision", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.other.lane_invasion", - "id": "lane_invasion", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.pseudo.tf", - "id": "tf" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - }, - { - "type": "sensor.pseudo.speedometer", - "id": "speedometer" - }, - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "vehicle.audi.a2", - "id": "npc_vehicle_1", - "spawn_point": {"x": 60.0, "y": 2.0, "z": 1.37, "roll": 0.0, "pitch": 0.0, "yaw": 180.0}, - "sensors": - [ - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - } - ] - } - ] -} \ No newline at end of file diff --git a/behavior_metrics/configs/DL-tensorflow.yml b/behavior_metrics/configs/gazebo/DL-tensorflow.yml similarity index 96% rename from behavior_metrics/configs/DL-tensorflow.yml rename to behavior_metrics/configs/gazebo/DL-tensorflow.yml index 84e4a0c6..9383c7cd 100644 --- a/behavior_metrics/configs/DL-tensorflow.yml +++ b/behavior_metrics/configs/gazebo/DL-tensorflow.yml @@ -17,7 +17,7 @@ Behaviors: MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_keras.py' + BrainPath: 'brains/gazebo/f1/brain_f1_keras.py' PilotTimeCycle: 50 Parameters: Model: '[model_name].h5' diff --git a/behavior_metrics/configs/DL-torch-lstm.yml b/behavior_metrics/configs/gazebo/DL-torch-lstm.yml similarity index 95% rename from behavior_metrics/configs/DL-torch-lstm.yml rename to behavior_metrics/configs/gazebo/DL-torch-lstm.yml index 8f7d639e..38c12de0 100644 --- a/behavior_metrics/configs/DL-torch-lstm.yml +++ b/behavior_metrics/configs/gazebo/DL-torch-lstm.yml @@ -16,7 +16,7 @@ Behaviors: Topic: '/F1ROS/cmd_vel' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_torch-lstm.py' + BrainPath: 'brains/gazebo/ssf1/brain_f1_torch-lstm.py' PilotTimeCycle: 50 Parameters: Model: 'model_lstm_pilotnet_torch.ckpt' diff --git a/behavior_metrics/configs/DL-torch-stacked.yml b/behavior_metrics/configs/gazebo/DL-torch-stacked.yml similarity index 95% rename from behavior_metrics/configs/DL-torch-stacked.yml rename to behavior_metrics/configs/gazebo/DL-torch-stacked.yml index ec6432b1..87b7c122 100644 --- a/behavior_metrics/configs/DL-torch-stacked.yml +++ b/behavior_metrics/configs/gazebo/DL-torch-stacked.yml @@ -16,7 +16,7 @@ Behaviors: Topic: '/F1ROS/cmd_vel' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_torchstacked.py' + BrainPath: 'brains/gazebo/f1/brain_f1_torchstacked.py' PilotTimeCycle: 50 Parameters: Model: 'model_pilotnet_torch_h5_extreme.ckpt' diff --git a/behavior_metrics/configs/DL-torch.yml b/behavior_metrics/configs/gazebo/DL-torch.yml similarity index 96% rename from behavior_metrics/configs/DL-torch.yml rename to behavior_metrics/configs/gazebo/DL-torch.yml index 6ddf6782..8b9f1ea6 100644 --- a/behavior_metrics/configs/DL-torch.yml +++ b/behavior_metrics/configs/gazebo/DL-torch.yml @@ -16,7 +16,7 @@ Behaviors: Topic: '/F1ROS/cmd_vel' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_torch.py' + BrainPath: 'brains/gazebo/f1/brain_f1_torch.py' PilotTimeCycle: 50 Parameters: Model: 'baseline.pth' diff --git a/behavior_metrics/configs/default-drone.yml b/behavior_metrics/configs/gazebo/default-drone.yml similarity index 100% rename from behavior_metrics/configs/default-drone.yml rename to behavior_metrics/configs/gazebo/default-drone.yml diff --git a/behavior_metrics/configs/default-multiple.yml b/behavior_metrics/configs/gazebo/default-multiple.yml similarity index 93% rename from behavior_metrics/configs/default-multiple.yml rename to behavior_metrics/configs/gazebo/default-multiple.yml index 58da4295..d8facdb9 100644 --- a/behavior_metrics/configs/default-multiple.yml +++ b/behavior_metrics/configs/gazebo/default-multiple.yml @@ -16,7 +16,7 @@ Behaviors: Topic: '/F1ROS/cmd_vel' MaxV: 3 MaxW: 0.3 - BrainPath: ['brains/f1/brain_f1_follow_line_dqn.py', 'brains/f1/brain_f1_follow_line_qlearn.py'] + BrainPath: ['brains/gazebo/f1/brain_f1_follow_line_dqn.py', 'brains/gazebo/f1/brain_f1_follow_line_qlearn.py'] PilotTimeCycle: 50 Parameters: # Model: ['model_deepest_lstm_cropped_250_norm_max_pooling.h5', 'model_deepest_lstm_cropped_250_norm_test.h5'] diff --git a/behavior_metrics/configs/default-rl-dqn.yml b/behavior_metrics/configs/gazebo/default-rl-dqn.yml similarity index 95% rename from behavior_metrics/configs/default-rl-dqn.yml rename to behavior_metrics/configs/gazebo/default-rl-dqn.yml index a9fa160c..60e51aa4 100644 --- a/behavior_metrics/configs/default-rl-dqn.yml +++ b/behavior_metrics/configs/gazebo/default-rl-dqn.yml @@ -17,7 +17,7 @@ Behaviors: MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_follow_line_dqn.py' + BrainPath: 'brains/gazebo/f1/brain_f1_follow_line_dqn.py' PilotTimeCycle: 50 Parameters: ImageTranform: '' diff --git a/behavior_metrics/configs/default-rl-qlearn.yml b/behavior_metrics/configs/gazebo/default-rl-qlearn.yml similarity index 94% rename from behavior_metrics/configs/default-rl-qlearn.yml rename to behavior_metrics/configs/gazebo/default-rl-qlearn.yml index 1f220904..43c1f04e 100644 --- a/behavior_metrics/configs/default-rl-qlearn.yml +++ b/behavior_metrics/configs/gazebo/default-rl-qlearn.yml @@ -17,7 +17,7 @@ Behaviors: MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_follow_line_qlearn.py' + BrainPath: 'brains/gazebo/f1/brain_f1_follow_line_qlearn.py' PilotTimeCycle: 50 Parameters: ImageTranform: '' diff --git a/behavior_metrics/configs/default-rl.yml b/behavior_metrics/configs/gazebo/default-rl.yml similarity index 100% rename from behavior_metrics/configs/default-rl.yml rename to behavior_metrics/configs/gazebo/default-rl.yml diff --git a/behavior_metrics/configs/default.yml b/behavior_metrics/configs/gazebo/default.yml similarity index 95% rename from behavior_metrics/configs/default.yml rename to behavior_metrics/configs/gazebo/default.yml index ee29f3be..65e26565 100644 --- a/behavior_metrics/configs/default.yml +++ b/behavior_metrics/configs/gazebo/default.yml @@ -17,7 +17,7 @@ Behaviors: MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_opencv.py' + BrainPath: 'brains/gazebo/f1/brain_f1_opencv.py' PilotTimeCycle: 50 Parameters: ImageTranform: '' diff --git a/behavior_metrics/configs/torch-multiple.yml b/behavior_metrics/configs/gazebo/torch-multiple.yml similarity index 90% rename from behavior_metrics/configs/torch-multiple.yml rename to behavior_metrics/configs/gazebo/torch-multiple.yml index 8510feed..cf50acab 100644 --- a/behavior_metrics/configs/torch-multiple.yml +++ b/behavior_metrics/configs/gazebo/torch-multiple.yml @@ -16,7 +16,7 @@ Behaviors: Topic: '/F1ROS/cmd_vel' MaxV: 3 MaxW: 0.3 - BrainPath: ['brains/f1/brain_f1_torch.py', 'brains/f1/brain_f1_torch.py', 'brains/f1/brain_f1_torch.py', 'brains/f1/brain_f1_torch.py', 'brains/f1/brain_f1_torch.py'] + BrainPath: ['brains/gazebo/f1/brain_f1_torch.py', 'brains/gazebo/f1/brain_f1_torch.py', 'brains/gazebo/f1/brain_f1_torch.py', 'brains/gazebo/f1/brain_f1_torch.py', 'brains/gazebo/f1/brain_f1_torch.py'] PilotTimeCycle: 50 Parameters: Model: ['model_pilotnet_torch.ckpt', 'model_pilotnet_torch.ckpt', 'model_pilotnet_torch.ckpt', 'model_pilotnet_torch.ckpt', 'model_pilotnet_torch.ckpt'] diff --git a/behavior_metrics/driver_carla.py b/behavior_metrics/driver_carla.py index 9a27a9bc..088cd59e 100644 --- a/behavior_metrics/driver_carla.py +++ b/behavior_metrics/driver_carla.py @@ -7,9 +7,10 @@ import glob import json -from pilot_carla import PilotCarla + from ui.tui.main_view import TUI from utils import environment +from utils.traffic import TrafficManager from utils.colors import Colors from utils.configuration import Config from utils.controller_carla import ControllerCarla @@ -17,11 +18,11 @@ from utils.tmp_world_generator import tmp_world_generator from utils import metrics_carla from datetime import datetime +from pilot_carla import PilotCarla import matplotlib.pyplot as plt import pandas as pd - def check_args(argv): """Function that handles argument checking and parsing. @@ -281,6 +282,12 @@ def main(): if not config_data['script']: environment.launch_env(app_configuration.current_world, random_spawn_point=app_configuration.experiment_random_spawn_point, carla_simulator=True) controller = ControllerCarla() + traffic_manager = TrafficManager(app_configuration.number_of_vehicle, + app_configuration.number_of_walker, + app_configuration.percentage_walker_running, + app_configuration.percentage_walker_crossing, + app_configuration.async_mode) + traffic_manager.generate_traffic() # Launch control if hasattr(app_configuration, 'experiment_model'): @@ -293,6 +300,7 @@ def main(): logger.info('Executing app') main_win(app_configuration, controller) logger.info('closing all processes...') + traffic_manager.destroy() pilot.kill_event.set() environment.close_ros_and_simulators() else: diff --git a/behavior_metrics/models/carla_tf_models/20221214-102705_deepestLSTMTinyPilotNet_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_both_directions_all_towns_PAPER_cp.h5 b/behavior_metrics/models/carla_tf_models/20221214-102705_deepestLSTMTinyPilotNet_CARLA_14_12_dataset_bird_eye_300_epochs_no_flip_3_output_both_directions_all_towns_PAPER_cp.h5 deleted file mode 100644 index 8d73f5eeda2013dff2580a9b334f5ebf6d161e33..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 986592 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a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/fingerprint.pb b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/fingerprint.pb similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/fingerprint.pb rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/fingerprint.pb diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/keras_metadata.pb b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/keras_metadata.pb similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/keras_metadata.pb rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/keras_metadata.pb diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/saved_model.pb b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/saved_model.pb similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/saved_model.pb rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/saved_model.pb diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.data-00000-of-00001 b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.data-00000-of-00001 similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.data-00000-of-00001 rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.data-00000-of-00001 diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.index b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.index similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5334_Epoch596_inTime20230310-223500.model/variables/variables.index rename to 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index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/keras_metadata.pb rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/keras_metadata.pb diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/saved_model.pb b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/saved_model.pb similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/saved_model.pb rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/saved_model.pb diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.data-00000-of-00001 b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.data-00000-of-00001 similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.data-00000-of-00001 rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.data-00000-of-00001 diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.index b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.index similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.index rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max569_Epoch1455_inTime20230413-103523.model/variables/variables.index diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/fingerprint.pb b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/fingerprint.pb similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/fingerprint.pb rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/fingerprint.pb diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/keras_metadata.pb b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/keras_metadata.pb similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/keras_metadata.pb rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/keras_metadata.pb diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/saved_model.pb b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/saved_model.pb similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/saved_model.pb rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/saved_model.pb diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.data-00000-of-00001 b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.data-00000-of-00001 similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.data-00000-of-00001 rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.data-00000-of-00001 diff --git a/behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.index b/behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.index similarity index 100% rename from behavior_metrics/models/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.index rename to behavior_metrics/models/gazebo/rl_models/dqn/DQN_sp_16x16_LAPCOMPLETED_Max5742_Epoch591_inTime20230217-100807.model/variables/variables.index diff --git a/behavior_metrics/models/rl_models/qlearn/20230216-170351_Circuit-simple_States-sp1_Actions-simple_Rewards-followline_center_epsilon-0.05_epoch-4751_step-15001_reward-139266-qtable.npy b/behavior_metrics/models/gazebo/rl_models/qlearn/20230216-170351_Circuit-simple_States-sp1_Actions-simple_Rewards-followline_center_epsilon-0.05_epoch-4751_step-15001_reward-139266-qtable.npy similarity index 100% rename from behavior_metrics/models/rl_models/qlearn/20230216-170351_Circuit-simple_States-sp1_Actions-simple_Rewards-followline_center_epsilon-0.05_epoch-4751_step-15001_reward-139266-qtable.npy rename to behavior_metrics/models/gazebo/rl_models/qlearn/20230216-170351_Circuit-simple_States-sp1_Actions-simple_Rewards-followline_center_epsilon-0.05_epoch-4751_step-15001_reward-139266-qtable.npy diff --git a/behavior_metrics/models/gazebo/tf_models/tf_models.txt b/behavior_metrics/models/gazebo/tf_models/tf_models.txt new file mode 100644 index 00000000..e69de29b diff --git a/behavior_metrics/models/torch_models/model_lstm_pilotnet_torch.ckpt b/behavior_metrics/models/gazebo/torch_models/model_lstm_pilotnet_torch.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_lstm_pilotnet_torch.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_lstm_pilotnet_torch.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_extreme.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_extreme.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_extreme.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_extreme.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_fullimg_extreme.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_fullimg_extreme.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_fullimg_extreme.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_fullimg_extreme.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_h2.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h2.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_h2.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h2.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_h2_extreme.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h2_extreme.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_h2_extreme.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h2_extreme.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_h3_extreme.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h3_extreme.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_h3_extreme.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h3_extreme.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_h4.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h4.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_h4.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h4.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_h4_extreme.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h4_extreme.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_h4_extreme.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h4_extreme.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_h5_extreme.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h5_extreme.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_h5_extreme.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_h5_extreme.ckpt diff --git a/behavior_metrics/models/torch_models/model_pilotnet_torch_nocrop.ckpt b/behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_nocrop.ckpt similarity index 100% rename from behavior_metrics/models/torch_models/model_pilotnet_torch_nocrop.ckpt rename to behavior_metrics/models/gazebo/torch_models/model_pilotnet_torch_nocrop.ckpt diff --git a/behavior_metrics/pilot_carla.py b/behavior_metrics/pilot_carla.py index 15df0bf6..dff9c27e 100644 --- a/behavior_metrics/pilot_carla.py +++ b/behavior_metrics/pilot_carla.py @@ -153,6 +153,7 @@ def run(self): logger.error(e) except Exception as ex: logger.warning(type(ex).__name__) + logger.warning(ex) logger.warning('ERROR Pilot Carla!') self.stop() self.kill() @@ -165,6 +166,8 @@ def run(self): time.sleep((self.time_cycle - ms) / 1000.0) self.real_time_factors.append(self.real_time_factor) self.brain_iterations_simulated_time.append(self.ros_clock_time - start_time_ros) + if not self.async_mode: + self.controller.world.tick() self.execution_completed = True self.kill() logger.info('Pilot: pilot killed.') diff --git a/behavior_metrics/profiles/default.yml b/behavior_metrics/profiles/default.yml index 7e9f6644..d092cc9b 100644 --- a/behavior_metrics/profiles/default.yml +++ b/behavior_metrics/profiles/default.yml @@ -16,7 +16,7 @@ Behaviors: Topic: '/F1ROS/cmd_vel' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_opencv.py' + BrainPath: 'brains/gazebo/f1/brain_f1_opencv.py' Type: 'f1' Simulation: World: /opt/jderobot/share/jderobot/gazebo/launch/simple_circuit.launch diff --git a/behavior_metrics/robot/configurations/f1.yml b/behavior_metrics/robot/configurations/f1.yml index da76327b..21454dd7 100644 --- a/behavior_metrics/robot/configurations/f1.yml +++ b/behavior_metrics/robot/configurations/f1.yml @@ -15,5 +15,5 @@ Robot: Topic: '/F1ROS/cmd_vel' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_opencv.py' + BrainPath: 'brains/gazebo/f1/brain_f1_opencv.py' Type: 'formula1' \ No newline at end of file diff --git a/behavior_metrics/robot/configurations/f1_laser.yml b/behavior_metrics/robot/configurations/f1_laser.yml index 4c122006..591a3a93 100644 --- a/behavior_metrics/robot/configurations/f1_laser.yml +++ b/behavior_metrics/robot/configurations/f1_laser.yml @@ -19,5 +19,5 @@ Robot: Topic: '/F1ROS/cmd_vel' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_opencv.py' + BrainPath: 'brains/gazebo/f1/brain_f1_opencv.py' Type: 'formula1' \ No newline at end of file diff --git a/behavior_metrics/robot/configurations/turtlebot_laser.yml b/behavior_metrics/robot/configurations/turtlebot_laser.yml index 47e71a89..44f5c67d 100644 --- a/behavior_metrics/robot/configurations/turtlebot_laser.yml +++ b/behavior_metrics/robot/configurations/turtlebot_laser.yml @@ -22,5 +22,5 @@ Robot: Topic: '/turtlebotROS/mobile_base/commands/velocity' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/f1/brain_f1_opencv2.py' + BrainPath: 'brains/gazebo/f1/brain_f1_opencv2.py' Type: 'turtlebot' \ No newline at end of file diff --git a/behavior_metrics/robot/interfaces/birdeyeview.py b/behavior_metrics/robot/interfaces/birdeyeview.py index 8d07dc0d..2a237a60 100644 --- a/behavior_metrics/robot/interfaces/birdeyeview.py +++ b/behavior_metrics/robot/interfaces/birdeyeview.py @@ -10,13 +10,17 @@ def __init__(self): client, # carla.Client target_size=PixelDimensions(width=100, height=300), pixels_per_meter=10, + render_lanes_on_junctions=True, crop_type=BirdViewCropType.FRONT_AREA_ONLY ) def getImage(self, vehicle): - birdview = self.birdview_producer.produce( - agent_vehicle=vehicle # carla.Actor (spawned vehicle) - ) + try: + birdview = self.birdview_producer.produce( + agent_vehicle=vehicle # carla.Actor (spawned vehicle) + ) + except Exception as ex: + print(ex) # Mask to RGB image image = BirdViewProducer.as_rgb(birdview) return image diff --git a/behavior_metrics/ui/tui/main_view.py b/behavior_metrics/ui/tui/main_view.py index 669fceb1..ebd23136 100644 --- a/behavior_metrics/ui/tui/main_view.py +++ b/behavior_metrics/ui/tui/main_view.py @@ -12,7 +12,7 @@ # This application class serves as a wrapper for the initialization of curses # and also manages the actual forms of the application -brains_dir = ROOT_PATH + '/brains/f1/brain_f1_opencv.py' +brains_dir = ROOT_PATH + '/brains/gazebo/f1/brain_f1_opencv.py' dset_dir = ROOT_PATH + '/datasets/' logs_dir = ROOT_PATH + '/logs/' logs_path = ROOT_PATH + '/logs/log.log' diff --git a/behavior_metrics/utils/configuration.py b/behavior_metrics/utils/configuration.py index f475e32f..02adf75a 100644 --- a/behavior_metrics/utils/configuration.py +++ b/behavior_metrics/utils/configuration.py @@ -140,8 +140,23 @@ def initialize_configuration(self, config_data): self.spawn_points = config_data['Behaviors']['Simulation']['SpawnPoints'] else: self.spawn_points = [] - if 'MultiCar' in config_data['Behaviors']['Simulation']: - self.multicar = config_data['Behaviors']['Simulation']['MultiCar'] + + if 'NumberOfVehicle' in config_data['Behaviors']['Simulation']: + self.number_of_vehicle = config_data['Behaviors']['Simulation']['NumberOfVehicle'] + else: + self.number_of_vehicle = 0 + if 'NumberOfWalker' in config_data['Behaviors']['Simulation']: + self.number_of_walker = config_data['Behaviors']['Simulation']['NumberOfWalker'] + else: + self.number_of_walker = 0 + if 'PercentagePedestriansRunning' in config_data['Behaviors']['Simulation']: + self.percentage_walker_running = config_data['Behaviors']['Simulation']['PercentagePedestriansRunning'] + else: + self.percentage_walker_running = 0.0 + if 'PercentagePedestriansCrossing' in config_data['Behaviors']['Simulation']: + self.percentage_walker_crossing = config_data['Behaviors']['Simulation']['PercentagePedestriansCrossing'] + else: + self.percentage_walker_crossing = 0.0 if self.robot_type == 'f1rl': self.action_set = robot['Parameters']['action_set'] diff --git a/behavior_metrics/utils/controller_carla.py b/behavior_metrics/utils/controller_carla.py index e6c1f4e4..f8dad47a 100644 --- a/behavior_metrics/utils/controller_carla.py +++ b/behavior_metrics/utils/controller_carla.py @@ -26,13 +26,11 @@ import rosbag import json import math - from utils.logger import logger try: import carla except ModuleNotFoundError as ex: logger.error('CARLA is not supported') - from std_srvs.srv import Empty from sensor_msgs.msg import Image from cv_bridge import CvBridge @@ -45,7 +43,6 @@ except ModuleNotFoundError as ex: logger.error('CARLA is not supported') from PIL import Image - __author__ = 'sergiopaniego' __contributors__ = [] __license__ = 'GPLv3' @@ -312,7 +309,7 @@ def stop_recording_metrics(self): target_brain_iterations_real_time = 1 / (self.pilot.time_cycle / 1000) - if self.pilot.brains.active_brain.cameras_first_images != []: + if hasattr(self.pilot.brains.active_brain, 'cameras_first_images') and self.pilot.brains.active_brain.cameras_first_images != []: first_images = self.pilot.brains.active_brain.cameras_first_images last_images = self.pilot.brains.active_brain.cameras_last_images else: diff --git a/behavior_metrics/utils/metrics_carla.py b/behavior_metrics/utils/metrics_carla.py index c1154e93..3237e573 100644 --- a/behavior_metrics/utils/metrics_carla.py +++ b/behavior_metrics/utils/metrics_carla.py @@ -594,7 +594,9 @@ def get_per_model_aggregated_metrics(result, experiments_starting_time_str, expe fig.tight_layout() plt.xticks(rotation=90) plt.legend(handles=color_handles) - plt.savefig(experiments_starting_time_str + '/' + unique_experiment_model + '_ ' + experiment_metric_and_title['metric'] + '.png') + if len(unique_experiment_model.split('/')) > 1: + unique_experiment_model = unique_experiment_model.split('/')[-1] + plt.savefig(experiments_starting_time_str + '/' + unique_experiment_model + '_' + experiment_metric_and_title['metric'] + '.png') plt.close() def get_all_experiments_aggregated_metrics_boxplot(result, experiments_starting_time_str, experiments_metrics_and_titles): diff --git a/behavior_metrics/utils/traffic.py b/behavior_metrics/utils/traffic.py new file mode 100644 index 00000000..e910f19f --- /dev/null +++ b/behavior_metrics/utils/traffic.py @@ -0,0 +1,201 @@ +# Modified based on: https://github.com/carla-simulator/carla/blob/master/PythonAPI/examples/generate_traffic.py +import carla +from utils.logger import logger +import random + +spawn_actor = carla.command.SpawnActor +set_autopilot = carla.command.SetAutopilot +future_actor = carla.command.FutureActor + +class TrafficManager: + def __init__(self, n_vehicle, n_walker, percentage_walker_running=0.0, percentage_walker_crossing=0.0, async_mode=False, port=8000): + self.client = carla.Client('localhost', 2000) + self.world = self.client.get_world() + if not async_mode: + settings = self.world.get_settings() + settings.synchronous_mode = True + self.world.apply_settings(settings) + + traffic_manager = self.client.get_trafficmanager(port) + traffic_manager.set_synchronous_mode(True) + traffic_manager.set_global_distance_to_leading_vehicle(2.5) + traffic_manager.set_hybrid_physics_mode(True) + traffic_manager.set_hybrid_physics_radius(70.0) + self.traffic_manager = traffic_manager + + self.n_vehicle = n_vehicle + self.n_walker = n_walker + self.percentage_walker_running = percentage_walker_running + self.percentage_walker_crossing = percentage_walker_crossing + + self.vehicles = [] + self.walkers = [] + self.walker_actors = [] + self.walker_ids = [] + + def generate_traffic(self): + if self.n_vehicle > 0: + self.spawn_vehicles(self.world, self.client, self.n_vehicle, self.traffic_manager) + if self.n_walker > 0: + self.spawn_pedestrians(self.world, self.client, self.n_walker, + percentagePedestriansRunning=self.percentage_walker_running, + percentagePedestriansCrossing=self.percentage_walker_crossing) + logger.info('spawned %d vehicles and %d walkers.' % (len(self.vehicles), len(self.walkers))) + + def get_actor_blueprints(self, world, filter, generation): + bps = world.get_blueprint_library().filter(filter) + + if generation.lower() == "all": + return bps + + # If the filter returns only one bp, we assume that this one needed and therefore, we ignore the generation + if len(bps) == 1: + return bps + + try: + int_generation = int(generation) + if int_generation in [1, 2]: + bps = [x for x in bps if int(x.get_attribute('generation')) == int_generation] + return bps + else: + print(" Warning! Actor Generation is not valid. No actor will be spawned.") + return [] + except: + print(" Warning! Actor Generation is not valid. No actor will be spawned.") + return [] + + + def get_pedestrain_spawn_points(self, world, n): + spawn_points = [] + for i in range(n): + spawn_point = carla.Transform() + loc = world.get_random_location_from_navigation() + if (loc != None): + spawn_point.location = loc + spawn_points.append(spawn_point) + return spawn_points + + + def get_vehicle_spawn_points(self, world, n_vehicles): + spawn_points = world.get_map().get_spawn_points() + number_of_spawn_points = len(spawn_points) + if n_vehicles < number_of_spawn_points: + random.shuffle(spawn_points) + elif n_vehicles > number_of_spawn_points: + msg = 'requested %d vehicles, but could only find %d spawn points' + logger.warning(msg, n_vehicles, number_of_spawn_points) + n_vehicles = number_of_spawn_points + return spawn_points + + def spawn_vehicles(self, world, client, n_vehicles, traffic_manager): + blueprints = self.get_actor_blueprints(world, 'vehicle.*', 'All') + # blueprints = [x for x in blueprints if x.get_attribute('base_type') == 'car'] # cars only + blueprints = sorted(blueprints, key=lambda bp: bp.id) + spawn_points = self.get_vehicle_spawn_points(world, n_vehicles) + + vehicles_list = [] + batch = [] + for n, transform in enumerate(spawn_points): + if n >= n_vehicles: + break + blueprint = random.choice(blueprints) + if blueprint.has_attribute('color'): + color = random.choice(blueprint.get_attribute('color').recommended_values) + blueprint.set_attribute('color', color) + if blueprint.has_attribute('driver_id'): + driver_id = random.choice(blueprint.get_attribute('driver_id').recommended_values) + blueprint.set_attribute('driver_id', driver_id) + blueprint.set_attribute('role_name', 'autopilot') + + batch.append(spawn_actor(blueprint, transform) + .then(set_autopilot(future_actor, True, traffic_manager.get_port()))) + + for response in client.apply_batch_sync(batch, True): + if response.error: + logger.error(response.error) + else: + vehicles_list.append(response.actor_id) + + self.vehicles = vehicles_list + + def spawn_pedestrians(self, world, client, n_pedestrians, percentagePedestriansRunning=0.0, percentagePedestriansCrossing=0.0): + walkers_list = [] + all_id = [] + + # 1. get spawn points and blueprints + spawn_points = self.get_pedestrain_spawn_points(world, n_pedestrians) + blueprintsWalkers = self.get_actor_blueprints(world, 'walker.pedestrian.*', '2') + + # 2. we spawn the walker object + batch = [] + walker_speed = [] + for spawn_point in spawn_points: + walker_bp = random.choice(blueprintsWalkers) + # set as not invincible + if walker_bp.has_attribute('is_invincible'): + walker_bp.set_attribute('is_invincible', 'false') + # set the max speed + if walker_bp.has_attribute('speed'): + if (random.random() > percentagePedestriansRunning): + # walking + walker_speed.append(walker_bp.get_attribute('speed').recommended_values[1]) + else: + # running + walker_speed.append(walker_bp.get_attribute('speed').recommended_values[2]) + else: + print("Walker has no speed") + walker_speed.append(0.0) + batch.append(spawn_actor(walker_bp, spawn_point)) + results = client.apply_batch_sync(batch, True) + walker_speed2 = [] + for i in range(len(results)): + if results[i].error: + logger.error(results[i].error) + else: + walkers_list.append({"id": results[i].actor_id}) + walker_speed2.append(walker_speed[i]) + walker_speed = walker_speed2 + # 3. we spawn the walker controller + batch = [] + walker_controller_bp = world.get_blueprint_library().find('controller.ai.walker') + for i in range(len(walkers_list)): + batch.append(spawn_actor(walker_controller_bp, carla.Transform(), walkers_list[i]["id"])) + results = client.apply_batch_sync(batch, True) + for i in range(len(results)): + if results[i].error: + logger.error(results[i].error) + else: + walkers_list[i]["con"] = results[i].actor_id + # 4. we put together the walkers and controllers id to get the objects from their id + for i in range(len(walkers_list)): + all_id.append(walkers_list[i]["con"]) + all_id.append(walkers_list[i]["id"]) + all_actors = world.get_actors(all_id) + + # wait for a tick to ensure client receives the last transform of the walkers we have just created + world.tick() + + # 5. initialize each controller and set target to walk to (list is [controller, actor, controller, actor ...]) + # set how many pedestrians can cross the road + world.set_pedestrians_cross_factor(percentagePedestriansCrossing) + for i in range(0, len(all_id), 2): + # start walker + all_actors[i].start() + # set walk to random point + all_actors[i].go_to_location(world.get_random_location_from_navigation()) + # max speed + all_actors[i].set_max_speed(float(walker_speed[int(i/2)])) + + self.walkers = walkers_list + self.walker_actors = all_actors + self.walker_ids = all_id + + def destroy(self): + logger.info('destroying %d vehicles' % len(self.vehicles)) + self.client.apply_batch([carla.command.DestroyActor(x) for x in self.vehicles]) + + for i in range(0, len(self.walker_ids), 2): + self.walker_actors[i].stop() + + logger.info('destroying %d walkers' % len(self.walkers)) + self.client.apply_batch([carla.command.DestroyActor(x) for x in self.walker_ids]) diff --git a/requirements.txt b/requirements.txt index fff71eb4..87b6ecc6 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,6 +1,6 @@ PyQt5==5.15.0 pyQt5-sip==12.8.1 -scipy==1.4.1 +scipy==1.10.0 jupyterlab==2.2.10 PyQt3D==5.15.0 npyscreen==4.10.5 @@ -19,7 +19,7 @@ netifaces==0.10.9 Pillow==9.3.0 pyglet==1.5.0 gym==0.17.3 -requests==2.21.0 +requests==2.31.0 six>=1.14.0 empy==3.3.2 vcstool==0.2.14 @@ -27,7 +27,7 @@ scikit-image==0.19.2 bagpy==0.4.10 pycryptodomex==3.9.9 torch==1.13.1 -torchvision==0.12.0 +torchvision==0.14.1 tensorboard==2.11.0 tensorboard-data-server==0.6.1 tensorboard-plugin-wit==1.8.0 From 0ccac91165d5ff5cfea77338452939e518578a2b Mon Sep 17 00:00:00 2001 From: enrique Date: Wed, 27 Sep 2023 18:09:44 +0200 Subject: [PATCH 03/12] readme --- README.md | 30 +++++++++++++++++++++++++++++- 1 file changed, 29 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 7f8ee756..456ab343 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,9 @@ The inner part of the brain can be controlled by an end-to-end model, written in The software provides two main pipelines, a graphical user interface (GUI) and a headless mode (scripted). The first one is intended for testing one brain+model at a time and debugging it visually while the headless mode is intended for running lots of experiments at the same time for comparison of a batch of brain+models in different scenarios. -architecture + +![alt text](./assets/behavior_metrics_paper_behavior_metrics_full_architecture.png) + ### Installation @@ -57,3 +59,29 @@ python3 driver_carla.py -c configs/CARLA/default_carla_multiple.yml -s If you want to contribute, please first check out [CONTRIBUTING.md](CONTRIBUTING.md) section. config + +### Evaluation modes + +Behavior Metrics provides two different evaluation modes, GUI evaluation and headless. + +#### GUI + +In this mode, activated with flag `-g`, the simulator and software application are displayed. + +![alt text](./assets/behavior_metrics_paper_behavior_metrics_gui.png) + +#### Headless + +In this mode, activated with flag `-s`, the evaluation is conducted without graphical interface. + +![alt text](./assets/behavior_metrics_paper_headless.png) + +### Robot controller + +The robot controller (brain folder) is the main controller of the ego vehicle. + +![alt text](./assets/behavior_metrics_paper_robot_controller.png) + +Behavior Metrics uses a publish/subscribe design to communicate with the simulator + +![alt text](./assets/behavior_metrics_publish_subscribe.png) From a1eb105f35ba0833ab3098ca3e7b905601cb68ae Mon Sep 17 00:00:00 2001 From: enrique Date: Thu, 28 Sep 2023 18:08:17 +0200 Subject: [PATCH 04/12] changed model and README --- README.md | 4 ---- .../configs/CARLA/default_carla_subjective_vision.yml | 2 +- 2 files changed, 1 insertion(+), 5 deletions(-) diff --git a/README.md b/README.md index 18c2bcdd..456ab343 100644 --- a/README.md +++ b/README.md @@ -84,8 +84,4 @@ The robot controller (brain folder) is the main controller of the ego vehicle. Behavior Metrics uses a publish/subscribe design to communicate with the simulator -<<<<<<< HEAD ![alt text](./assets/behavior_metrics_publish_subscribe.png) -======= -![alt text](./assets/behavior_metrics_publish_subscribe.png) ->>>>>>> upstream/noetic-devel diff --git a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml index 4d7a01b6..c72ab5d8 100644 --- a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml +++ b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml @@ -37,7 +37,7 @@ Behaviors: PilotTimeCycle: 100 AsyncMode: False Parameters: - Model: '20230517-094715_pilotnet_model_3_15+101_cp.h5' + Model: 'pilotnet_starstar_traffic_6.h5' ImageCropped: True ImageSize: [ 200,66 ] ImageNormalized: True From c73cce278f535cea130e3ba465f59ed217fd6221 Mon Sep 17 00:00:00 2001 From: enrique Date: Fri, 29 Sep 2023 17:47:16 +0200 Subject: [PATCH 05/12] added functionality to allow spawn of random traffic and spawn of controllable vehicles --- assets/behavior_metrics_full_architecture.png | Bin 120924 -> 0 bytes ...jective_vision_deep_learning_previous_v.py | 7 ++++-- .../CARLA_object_files/main_car.json | 16 ++++++++++++ .../town_02_anticlockwise_low.launch | 23 ++++++++++++------ .../CARLA/default_carla_subjective_vision.yml | 1 + behavior_metrics/utils/configuration.py | 5 ++++ behavior_metrics/utils/traffic.py | 8 +++++- 7 files changed, 49 insertions(+), 11 deletions(-) delete mode 100644 assets/behavior_metrics_full_architecture.png diff --git a/assets/behavior_metrics_full_architecture.png b/assets/behavior_metrics_full_architecture.png deleted file mode 100644 index d69552c040ae1bbd53a28d32d807753e37830508..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 120924 zcmeEv2i)XTx%UeDQ52+FP%bRZE6T2!lu1Tv%A`z9rcXd5lSwj3W|Em?CYcN%f-B;c zB4D{*D=HS6Aa+n(R6taat29BHfTA=(P!Q#N^6vY>u5$gn-?iZV$-c}aCnqPT{Ll0J zpXWI_^LDu+Z2!Vnyl~a3RohDpWu$NpOAS_ifWQ z`Wy402#T#mu(fEekwN#vXd(k2II<3*GU~?snq_#)1(yAVJsfKLp**n;fudgB$v}1n zj!L#So5S~<%Dyp+?+-`xcsw-PMz3hYb9n+I*J0W8mZI1wm-a(hI3C)r0bhclyMB5L zI|%#{r0|(cW*t;v=^1s+)B<~xBGNV(Q_b2~|6VzqWF|4bc0LKZZMtpLpt4KtjEo?( zeQ&v$nRW1Q4TV=d??#ncX+SjrXoJ)c1!|d%Ss~?t7l0FAwN)MlA^Z zc=K$gKU{A5a-K2ZV6)QGgu1Rl|1GtClWc9fKOHQ$f>^Fznp-q%Yq0X<46=M>q^)FL zP6!8D-;X!mzm)XH{kYPbf$u|kn~dGY3!8qXGlMmTX=ktWAy7H_okbqV@v-*dN>Vy*VyDrcIm%ouB?nN zKo4WaMqrPOsS%{lx4m>)Zj=crD975f-L%|uFfFIXGU}I-{`Byzj5N#}1BAmgNTAr2 z+q27EzdU8o6-dR;0uZH^^9(itABrz0YRjOvo+&%6^`8R_$g_;AKVARlg5PtEIXpLg z^k!q89Rj$QMhUJwJNVhjEJgj&g|*?5AV@_Q^fvSh2;-IOkY;X##ItD)7^@I2RE!ut zYyL>{p1lZ1R$4H8FFm=plECCex+PU>a7#Jgs7Y*nB@1-JGr2ZNOOds5^B-XshChAE zCIH(FI_zUh3(q~nz0@A)I6muvYa zh{THNu)-67g{>SyOa5o`1z`R^m@I6y(x_Dd(Fj{Dm+1=kPo9wiY?Hs|mgqRSY%8vi zj2yNOU1k)Upg6OF>`fuOVxT>L5WL)$%@CZ;55=ocgH|rG?{-wz6r@Q)`P^dLX@$ zn)1lyDsY486z%{b&cmOs1w(C}A6Oet?NNF#^euno+S=X_DzkR9Zk$?7An(%#{&mS{ zW`$2Kg9Jk|E39)|2u*$&av<#T^ ze4L)AVDU#I-vf({pAKdtkgln@#rM*WnjgL~h19w*O3{@8OLsh9yJ_m*5M1brXjujq ziec-h=a4`v*3YKs0@q+>IqUNWUn_|JhX$D5_tx6r@C(<1m|15IH87TaZykUN07HPk zH+8jUVJa}7yck#|G!Xg{vA=XxqAT1A^-50SvDvB z!6Z#zn`+>)-00^<`P5;JvUZE9)?%b6SUwH^RqD+_zG=acl%BHiuM6KCCy&HZn!<<` zw%$@CmbN659=LXzNDt#WKU}~87b@^c=9yeqp4QW2W{A{U1Eh)OMt!kA&__+WkM*(A zXgJfbiqq{d!_p|1s6;fAnY0c;zTT`cEz#CVH4`{|tHbMkFgW%3K;xBOG0rnZU+X9g z%1!)SP^bGLk!d!1nj{F?#A^#qr|8f9jNoI;Jg)?qVL$BpaSe)Sv6*qGTIi&v30avQ za)rty5;zAb5NuFy&M7VyDkO(X{Y-B>BJ}-GaOg7xL5dw2JpK%6QV>LDVtz40M^Oac zTm}c5EzOjq&Npv{xp`_tFGz*eV@9=#4XY$FkcH3CC6aESbRne2xX2Biq!$MYqsO9Z zRTq}zrjD3O$n1Lx+ z*I*V_!K7taP{iZ1$mEe8{3*&Vo_R|n%{mg`N>>LlUDmJx%+!H*M8?hQSvXBFK! 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a/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py b/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py index d9d46ec1..7b967041 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py +++ b/behavior_metrics/brains/CARLA/brain_carla_subjective_vision_deep_learning_previous_v.py @@ -77,7 +77,10 @@ def __init__(self, sensors, actuators, handler, model, config=None): self.world.unload_map_layer(carla.MapLayer.Particles) time.sleep(5) - self.vehicle = self.world.get_actors().filter('vehicle.*')[0] + self.vehicle = next( + (p for p in self.world.get_actors() if 'vehicle' in p.type_id and p.attributes.get('role_name') == 'ego_vehicle'), + None + ) if model: if not path.exists(PRETRAINED_MODELS + model): @@ -195,7 +198,7 @@ def execute(self): self.motors.sendThrottle(throttle) self.motors.sendSteer(steer) self.motors.sendBrake(break_command) - + if vehicle_speed >= 35: self.motors.sendThrottle(0.0) self.motors.sendBrake(0.0) diff --git a/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car.json b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car.json index d687d1c9..0a9d8fce 100644 --- a/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car.json +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car.json @@ -156,6 +156,22 @@ "id": "control" } ] + }, + { + "type": "vehicle.audi.a2", + "id": "npc_vehicle_1", + "spawn_point": {"x": 60.0, "y": 2.0, "z": 1.37, "roll": 0.0, "pitch": 0.0, "yaw": 180.0}, + "sensors": + [ + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.odom", + "id": "odometry" + } + ] } ] } diff --git a/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch index d9823d00..9fb43704 100644 --- a/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch @@ -19,7 +19,7 @@ - + @@ -62,13 +62,20 @@ - - - - - - - + + + + + + + + + + + + + + diff --git a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml index c72ab5d8..1e8eb2a6 100644 --- a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml +++ b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml @@ -49,6 +49,7 @@ Behaviors: Simulation: World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch RandomSpawnPoint: False + MultiCar: True Dataset: In: '/tmp/my_bag.bag' Out: '' diff --git a/behavior_metrics/utils/configuration.py b/behavior_metrics/utils/configuration.py index 02adf75a..156d2376 100644 --- a/behavior_metrics/utils/configuration.py +++ b/behavior_metrics/utils/configuration.py @@ -141,6 +141,11 @@ def initialize_configuration(self, config_data): else: self.spawn_points = [] + if 'MultiCar' in config_data['Behaviors']['Simulation']: + self.multicar = config_data['Behaviors']['Simulation']['MultiCar'] + else: + self.multicar = False + if 'NumberOfVehicle' in config_data['Behaviors']['Simulation']: self.number_of_vehicle = config_data['Behaviors']['Simulation']['NumberOfVehicle'] else: diff --git a/behavior_metrics/utils/traffic.py b/behavior_metrics/utils/traffic.py index e910f19f..4bb1680a 100644 --- a/behavior_metrics/utils/traffic.py +++ b/behavior_metrics/utils/traffic.py @@ -34,6 +34,11 @@ def __init__(self, n_vehicle, n_walker, percentage_walker_running=0.0, percentag self.walker_ids = [] def generate_traffic(self): + for p in self.world.get_actors(): + if 'vehicle' in p.type_id: + if p.attributes['role_name'] != 'ego_vehicle': + set_autopilot(p, True, self.traffic_manager.get_port()) + if self.n_vehicle > 0: self.spawn_vehicles(self.world, self.client, self.n_vehicle, self.traffic_manager) if self.n_walker > 0: @@ -105,7 +110,8 @@ def spawn_vehicles(self, world, client, n_vehicles, traffic_manager): if blueprint.has_attribute('driver_id'): driver_id = random.choice(blueprint.get_attribute('driver_id').recommended_values) blueprint.set_attribute('driver_id', driver_id) - blueprint.set_attribute('role_name', 'autopilot') + blueprint.set_attribute('role_name', 'npc_vehicle_1') + batch.append(spawn_actor(blueprint, transform) .then(set_autopilot(future_actor, True, traffic_manager.get_port()))) From f83c3bfab98f25062cf597e5120a0726fb89092e Mon Sep 17 00:00:00 2001 From: enrique Date: Mon, 2 Oct 2023 11:30:09 +0200 Subject: [PATCH 06/12] changed autopilot setting --- .../configs/CARLA/default_carla_subjective_vision.yml | 1 + behavior_metrics/utils/traffic.py | 4 ++-- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml index 1e8eb2a6..52fe1a0a 100644 --- a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml +++ b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml @@ -50,6 +50,7 @@ Behaviors: World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch RandomSpawnPoint: False MultiCar: True + NumberOfVehicle: 0 Dataset: In: '/tmp/my_bag.bag' Out: '' diff --git a/behavior_metrics/utils/traffic.py b/behavior_metrics/utils/traffic.py index 4bb1680a..09d9b6bf 100644 --- a/behavior_metrics/utils/traffic.py +++ b/behavior_metrics/utils/traffic.py @@ -37,7 +37,7 @@ def generate_traffic(self): for p in self.world.get_actors(): if 'vehicle' in p.type_id: if p.attributes['role_name'] != 'ego_vehicle': - set_autopilot(p, True, self.traffic_manager.get_port()) + p.set_autopilot(True, self.traffic_manager.get_port()) if self.n_vehicle > 0: self.spawn_vehicles(self.world, self.client, self.n_vehicle, self.traffic_manager) @@ -110,7 +110,7 @@ def spawn_vehicles(self, world, client, n_vehicles, traffic_manager): if blueprint.has_attribute('driver_id'): driver_id = random.choice(blueprint.get_attribute('driver_id').recommended_values) blueprint.set_attribute('driver_id', driver_id) - blueprint.set_attribute('role_name', 'npc_vehicle_1') + blueprint.set_attribute('role_name', 'autopilot') batch.append(spawn_actor(blueprint, transform) From 9b42e8d7102fe05be6ecfbf1b698ecd712e3ff55 Mon Sep 17 00:00:00 2001 From: enrique Date: Tue, 3 Oct 2023 09:49:44 +0200 Subject: [PATCH 07/12] added new metric and renamed subjective vision files --- .../CARLA_object_files/main_car.json | 16 -- .../single_ad_car_subjective_vision.json | 177 +++++++++++++++++ ...own_02_anticlockwise_single_ad_low.launch} | 33 +--- .../CARLA/default_carla_subjective_vision.yml | 2 +- .../single_ad_car_town02.json | 178 ++++++++++++++++++ behavior_metrics/utils/metrics_carla.py | 11 ++ 6 files changed, 368 insertions(+), 49 deletions(-) create mode 100644 behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/single_ad_car_subjective_vision.json rename behavior_metrics/configs/CARLA/CARLA_launch_files/{town_02_anticlockwise_low.launch => town_02_anticlockwise_single_ad_low.launch} (57%) create mode 100644 behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json diff --git a/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car.json b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car.json index 0a9d8fce..d687d1c9 100644 --- a/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car.json +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car.json @@ -156,22 +156,6 @@ "id": "control" } ] - }, - { - "type": "vehicle.audi.a2", - "id": "npc_vehicle_1", - "spawn_point": {"x": 60.0, "y": 2.0, "z": 1.37, "roll": 0.0, "pitch": 0.0, "yaw": 180.0}, - "sensors": - [ - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - } - ] } ] } diff --git a/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/single_ad_car_subjective_vision.json b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/single_ad_car_subjective_vision.json new file mode 100644 index 00000000..0a9d8fce --- /dev/null +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/single_ad_car_subjective_vision.json @@ -0,0 +1,177 @@ +{ + "objects": + [ + { + "type": "sensor.pseudo.traffic_lights", + "id": "traffic_lights" + }, + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.actor_list", + "id": "actor_list" + }, + { + "type": "sensor.pseudo.markers", + "id": "markers" + }, + { + "type": "sensor.pseudo.opendrive_map", + "id": "map" + }, + { + "type": "vehicle.tesla.model3", + "id": "ego_vehicle", + "sensors": + [ + { + "type": "sensor.camera.rgb", + "id": "rgb_front", + "spawn_point": {"x": 2.5, "y": 0.0, "z": 0.8, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "image_size_x": 640, + "image_size_y": 480 + }, + { + "type": "sensor.camera.rgb", + "id": "rgb_view", + "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, + "image_size_x": 800, + "image_size_y": 600, + "fov": 90.0, + "attached_objects": + [ + { + "type": "actor.pseudo.control", + "id": "control" + } + ] + }, + { + "type": "sensor.lidar.ray_cast", + "id": "lidar", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "range": 50, + "channels": 32, + "points_per_second": 320000, + "upper_fov": 2.0, + "lower_fov": -26.8, + "rotation_frequency": 20, + "noise_stddev": 0.0 + }, + { + "type": "sensor.lidar.ray_cast_semantic", + "id": "semantic_lidar", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "range": 50, + "channels": 32, + "points_per_second": 320000, + "upper_fov": 2.0, + "lower_fov": -26.8, + "rotation_frequency": 20 + }, + { + "type": "sensor.other.radar", + "id": "radar_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "horizontal_fov": 30.0, + "vertical_fov": 10.0, + "points_per_second": 1500, + "range": 100.0 + }, + { + "type": "sensor.camera.semantic_segmentation", + "id": "semantic_segmentation_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 400, + "image_size_y": 70 + }, + { + "type": "sensor.camera.depth", + "id": "depth_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 400, + "image_size_y": 70 + }, + { + "type": "sensor.camera.dvs", + "id": "dvs_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 400, + "image_size_y": 70, + "positive_threshold": 0.3, + "negative_threshold": 0.3, + "sigma_positive_threshold": 0.0, + "sigma_negative_threshold": 0.0, + "use_log": true, + "log_eps": 0.001 + }, + { + "type": "sensor.other.gnss", + "id": "gnss", + "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, + "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, + "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 + }, + { + "type": "sensor.other.imu", + "id": "imu", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, + "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, + "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 + }, + { + "type": "sensor.other.collision", + "id": "collision", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} + }, + { + "type": "sensor.other.lane_invasion", + "id": "lane_invasion", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} + }, + { + "type": "sensor.pseudo.tf", + "id": "tf" + }, + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.odom", + "id": "odometry" + }, + { + "type": "sensor.pseudo.speedometer", + "id": "speedometer" + }, + { + "type": "actor.pseudo.control", + "id": "control" + } + ] + }, + { + "type": "vehicle.audi.a2", + "id": "npc_vehicle_1", + "spawn_point": {"x": 60.0, "y": 2.0, "z": 1.37, "roll": 0.0, "pitch": 0.0, "yaw": 180.0}, + "sensors": + [ + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.odom", + "id": "odometry" + } + ] + } + ] +} diff --git a/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_low.launch similarity index 57% rename from behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_low.launch index 9fb43704..c0822290 100644 --- a/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_low.launch @@ -11,37 +11,6 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - @@ -62,7 +31,7 @@ - + diff --git a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml index 52fe1a0a..e9df8537 100644 --- a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml +++ b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_low.launch + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_low.launch RandomSpawnPoint: False MultiCar: True NumberOfVehicle: 0 diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json new file mode 100644 index 00000000..3438109a --- /dev/null +++ b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json @@ -0,0 +1,178 @@ +{ + "objects": + [ + { + "type": "sensor.pseudo.traffic_lights", + "id": "traffic_lights" + }, + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.actor_list", + "id": "actor_list" + }, + { + "type": "sensor.pseudo.markers", + "id": "markers" + }, + { + "type": "sensor.pseudo.opendrive_map", + "id": "map" + }, + { + "type": "vehicle.tesla.model3", + "id": "ego_vehicle", + "sensors": + [ + { + "type": "sensor.camera.rgb", + "id": "rgb_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "image_size_x": 800, + "image_size_y": 600, + "fov": 90.0 + }, + { + "type": "sensor.camera.rgb", + "id": "rgb_view", + "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, + "image_size_x": 800, + "image_size_y": 600, + "fov": 90.0, + "attached_objects": + [ + { + "type": "actor.pseudo.control", + "id": "control" + } + ] + }, + { + "type": "sensor.lidar.ray_cast", + "id": "lidar", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "range": 50, + "channels": 32, + "points_per_second": 320000, + "upper_fov": 2.0, + "lower_fov": -26.8, + "rotation_frequency": 20, + "noise_stddev": 0.0 + }, + { + "type": "sensor.lidar.ray_cast_semantic", + "id": "semantic_lidar", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "range": 50, + "channels": 32, + "points_per_second": 320000, + "upper_fov": 2.0, + "lower_fov": -26.8, + "rotation_frequency": 20 + }, + { + "type": "sensor.other.radar", + "id": "radar_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "horizontal_fov": 30.0, + "vertical_fov": 10.0, + "points_per_second": 1500, + "range": 100.0 + }, + { + "type": "sensor.camera.semantic_segmentation", + "id": "semantic_segmentation_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 400, + "image_size_y": 70 + }, + { + "type": "sensor.camera.depth", + "id": "depth_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 400, + "image_size_y": 70 + }, + { + "type": "sensor.camera.dvs", + "id": "dvs_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 400, + "image_size_y": 70, + "positive_threshold": 0.3, + "negative_threshold": 0.3, + "sigma_positive_threshold": 0.0, + "sigma_negative_threshold": 0.0, + "use_log": true, + "log_eps": 0.001 + }, + { + "type": "sensor.other.gnss", + "id": "gnss", + "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, + "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, + "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 + }, + { + "type": "sensor.other.imu", + "id": "imu", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, + "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, + "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 + }, + { + "type": "sensor.other.collision", + "id": "collision", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} + }, + { + "type": "sensor.other.lane_invasion", + "id": "lane_invasion", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} + }, + { + "type": "sensor.pseudo.tf", + "id": "tf" + }, + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.odom", + "id": "odometry" + }, + { + "type": "sensor.pseudo.speedometer", + "id": "speedometer" + }, + { + "type": "actor.pseudo.control", + "id": "control" + } + ] + }, + { + "type": "vehicle.audi.a2", + "id": "npc_vehicle_1", + "spawn_point": {"x": 194.0, "y": -250, "z": 1.37, "roll": 0.0, "pitch": 0.0, "yaw": 90.0}, + "sensors": + [ + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.odom", + "id": "odometry" + } + ] + } + ] +} \ No newline at end of file diff --git a/behavior_metrics/utils/metrics_carla.py b/behavior_metrics/utils/metrics_carla.py index 3237e573..d1ab3cb3 100644 --- a/behavior_metrics/utils/metrics_carla.py +++ b/behavior_metrics/utils/metrics_carla.py @@ -647,6 +647,12 @@ def get_distance_other_vehicle(experiment_metrics, checkpoints, checkpoints_2): medium_distance = 0 great_distance = 0 total_distance = 0 + + dangerous_distance_pct_km = 0 + close_distance_pct_km = 0 + medium_distance_pct_km = 0 + great_distance_pct_km = 0 + total_distance_pct_km = 0 for i, (point, point_2) in enumerate(zip(checkpoints, checkpoints_2)): current_checkpoint = np.array([point['pose.pose.position.x'], point['pose.pose.position.y']]) @@ -678,4 +684,9 @@ def get_distance_other_vehicle(experiment_metrics, checkpoints, checkpoints_2): experiment_metrics['great_distance_km'] = great_distance experiment_metrics['total_distance_to_front_car'] = total_distance + experiment_metrics['dangerous_distance_pct_km'] = total_distance and dangerous_distance / total_distance or 0 + experiment_metrics['close_distance_pct_km'] = total_distance and close_distance / total_distance or 0 + experiment_metrics['medium_distance_pct_km'] = total_distance and medium_distance / total_distance or 0 + experiment_metrics['great_distance_pct_km'] = total_distance and great_distance / total_distance or 0 + return experiment_metrics \ No newline at end of file From 9048f8d52ef33de23227c4010232fa2ffcaa6dc9 Mon Sep 17 00:00:00 2001 From: enrique Date: Tue, 3 Oct 2023 13:14:58 +0200 Subject: [PATCH 08/12] added new metric to BehaviorMetric visual output --- behavior_metrics/driver_carla.py | 18 +++++++++++++++++- behavior_metrics/ui/gui/views/stats_window.py | 8 ++++++++ behavior_metrics/utils/metrics_carla.py | 8 ++++---- 3 files changed, 29 insertions(+), 5 deletions(-) diff --git a/behavior_metrics/driver_carla.py b/behavior_metrics/driver_carla.py index 088cd59e..94a721d3 100644 --- a/behavior_metrics/driver_carla.py +++ b/behavior_metrics/driver_carla.py @@ -250,7 +250,23 @@ def generate_agregated_experiments_metrics(experiments_starting_time, experiment }, { 'metric': 'suddenness_distance_speed_per_km', - 'title': 'uddenness distance speed per km per experiment' + 'title': 'Suddenness distance speed per km per experiment' + }, + { + 'metric': 'dangerous_distance_pct_km', + 'title': 'Percentage of dangerous distance per km' + }, + { + 'metric': 'close_distance_pct_km', + 'title': 'Percentage of close distance per km' + }, + { + 'metric': 'medium_distance_pct_km', + 'title': 'Percentage of medium distance per km' + }, + { + 'metric': 'great_distance_pct_km', + 'title': 'Percentage of great distance per km' }, { 'metric': 'completed_laps', diff --git a/behavior_metrics/ui/gui/views/stats_window.py b/behavior_metrics/ui/gui/views/stats_window.py index 9155cbec..110b7554 100644 --- a/behavior_metrics/ui/gui/views/stats_window.py +++ b/behavior_metrics/ui/gui/views/stats_window.py @@ -128,5 +128,13 @@ def __init__(self, parent=None, controller=None): self.layout.addWidget(self.suddenness_distance_speed_label) self.suddenness_distance_speed_per_km_label = QLabel("Suddenness distance speed per km -> " + str(self.controller.experiment_metrics['suddenness_distance_speed_per_km'])) self.layout.addWidget(self.suddenness_distance_speed_per_km_label) + self.dangerous_distance_pct_km = QLabel("Percentage of dangerous distance per km -> " + str(self.controller.experiment_metrics['dangerous_distance_pct_km'])) + self.layout.addWidget(self.dangerous_distance_pct_km) + self.close_distance_pct_km = QLabel("Percentage of close distance per km -> " + str(self.controller.experiment_metrics['close_distance_pct_km'])) + self.layout.addWidget(self.close_distance_pct_km) + self.medium_distance_pct_km = QLabel("Percentage of medium distance per km -> " + str(self.controller.experiment_metrics['medium_distance_pct_km'])) + self.layout.addWidget(self.medium_distance_pct_km) + self.great_distance_pct_km = QLabel("Percentage of great distance per km -> " + str(self.controller.experiment_metrics['great_distance_pct_km'])) + self.layout.addWidget(self.great_distance_pct_km) wid.setLayout(self.layout) \ No newline at end of file diff --git a/behavior_metrics/utils/metrics_carla.py b/behavior_metrics/utils/metrics_carla.py index d1ab3cb3..3fa87434 100644 --- a/behavior_metrics/utils/metrics_carla.py +++ b/behavior_metrics/utils/metrics_carla.py @@ -684,9 +684,9 @@ def get_distance_other_vehicle(experiment_metrics, checkpoints, checkpoints_2): experiment_metrics['great_distance_km'] = great_distance experiment_metrics['total_distance_to_front_car'] = total_distance - experiment_metrics['dangerous_distance_pct_km'] = total_distance and dangerous_distance / total_distance or 0 - experiment_metrics['close_distance_pct_km'] = total_distance and close_distance / total_distance or 0 - experiment_metrics['medium_distance_pct_km'] = total_distance and medium_distance / total_distance or 0 - experiment_metrics['great_distance_pct_km'] = total_distance and great_distance / total_distance or 0 + experiment_metrics['dangerous_distance_pct_km'] = (total_distance and dangerous_distance / total_distance or 0) * 100 + experiment_metrics['close_distance_pct_km'] = (total_distance and close_distance / total_distance or 0) * 100 + experiment_metrics['medium_distance_pct_km'] = (total_distance and medium_distance / total_distance or 0) * 100 + experiment_metrics['great_distance_pct_km'] = (total_distance and great_distance / total_distance or 0) * 100 return experiment_metrics \ No newline at end of file From bbe19ee4ac2404d18dace034485ca5492822f473 Mon Sep 17 00:00:00 2001 From: sergiopaniego Date: Tue, 3 Oct 2023 16:18:30 +0200 Subject: [PATCH 09/12] Moved files and managed no multicar mode --- .../single_ad_car_town02.json | 0 ..._02_anticlockwise_single_ad_npc_low.launch | 0 .../CARLA/default_carla_subjective_vision.yml | 2 +- behavior_metrics/ui/gui/views/stats_window.py | 25 ++++++++++--------- behavior_metrics/utils/controller_carla.py | 17 +++++++++---- 5 files changed, 26 insertions(+), 18 deletions(-) rename behavior_metrics/configs/{ => CARLA}/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json (100%) rename behavior_metrics/configs/{ => CARLA}/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch (100%) diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json rename to behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/single_ad_car_town02.json diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch diff --git a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml index e9df8537..4a372d0a 100644 --- a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml +++ b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_low.launch + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch RandomSpawnPoint: False MultiCar: True NumberOfVehicle: 0 diff --git a/behavior_metrics/ui/gui/views/stats_window.py b/behavior_metrics/ui/gui/views/stats_window.py index 110b7554..bf2c2a8c 100644 --- a/behavior_metrics/ui/gui/views/stats_window.py +++ b/behavior_metrics/ui/gui/views/stats_window.py @@ -102,10 +102,10 @@ def __init__(self, parent=None, controller=None): self.layout.addWidget(self.mean_brain_iterations_simulated_time_label) self.brain_iterations_frequency_simulated_time_label = QLabel("Brain iterations frequency simulated time-> " + str(self.controller.experiment_metrics['brain_iterations_frequency_simulated_time']) + ' it/s') self.layout.addWidget(self.brain_iterations_frequency_simulated_time_label) - self.mean_inference_time_label = QLabel("GPU mean inference time -> " + str(self.controller.experiment_metrics['gpu_mean_inference_time']) + ' s') - self.layout.addWidget(self.mean_inference_time_label) - self.mean_inference_time_label = QLabel("GPU inference frequency -> " + str(self.controller.experiment_metrics['gpu_inference_frequency']) + ' it/s') - self.layout.addWidget(self.mean_inference_time_label) + self.gpu_mean_inference_time_label = QLabel("GPU mean inference time -> " + str(self.controller.experiment_metrics['gpu_mean_inference_time']) + ' s') + self.layout.addWidget(self.gpu_mean_inference_time_label) + self.gpu_inference_frequency_label = QLabel("GPU inference frequency -> " + str(self.controller.experiment_metrics['gpu_inference_frequency']) + ' it/s') + self.layout.addWidget(self.gpu_inference_frequency_label) self.gpu_inference_label = QLabel("GPU inference -> " + str(self.controller.experiment_metrics['gpu_inference'])) self.layout.addWidget(self.gpu_inference_label) self.suddenness_distance_control_commands_label = QLabel("Suddenness distance control commands -> " + str(self.controller.experiment_metrics['suddenness_distance_control_commands'])) @@ -128,13 +128,14 @@ def __init__(self, parent=None, controller=None): self.layout.addWidget(self.suddenness_distance_speed_label) self.suddenness_distance_speed_per_km_label = QLabel("Suddenness distance speed per km -> " + str(self.controller.experiment_metrics['suddenness_distance_speed_per_km'])) self.layout.addWidget(self.suddenness_distance_speed_per_km_label) - self.dangerous_distance_pct_km = QLabel("Percentage of dangerous distance per km -> " + str(self.controller.experiment_metrics['dangerous_distance_pct_km'])) - self.layout.addWidget(self.dangerous_distance_pct_km) - self.close_distance_pct_km = QLabel("Percentage of close distance per km -> " + str(self.controller.experiment_metrics['close_distance_pct_km'])) - self.layout.addWidget(self.close_distance_pct_km) - self.medium_distance_pct_km = QLabel("Percentage of medium distance per km -> " + str(self.controller.experiment_metrics['medium_distance_pct_km'])) - self.layout.addWidget(self.medium_distance_pct_km) - self.great_distance_pct_km = QLabel("Percentage of great distance per km -> " + str(self.controller.experiment_metrics['great_distance_pct_km'])) - self.layout.addWidget(self.great_distance_pct_km) + if hasattr(self.controller.experiment_metrics, 'dangerous_distance_pct_km'): + self.dangerous_distance_pct_km = QLabel("Percentage of dangerous distance per km -> " + str(self.controller.experiment_metrics['dangerous_distance_pct_km'])) + self.layout.addWidget(self.dangerous_distance_pct_km) + self.close_distance_pct_km = QLabel("Percentage of close distance per km -> " + str(self.controller.experiment_metrics['close_distance_pct_km'])) + self.layout.addWidget(self.close_distance_pct_km) + self.medium_distance_pct_km = QLabel("Percentage of medium distance per km -> " + str(self.controller.experiment_metrics['medium_distance_pct_km'])) + self.layout.addWidget(self.medium_distance_pct_km) + self.great_distance_pct_km = QLabel("Percentage of great distance per km -> " + str(self.controller.experiment_metrics['great_distance_pct_km'])) + self.layout.addWidget(self.great_distance_pct_km) wid.setLayout(self.layout) \ No newline at end of file diff --git a/behavior_metrics/utils/controller_carla.py b/behavior_metrics/utils/controller_carla.py index f8dad47a..5290a7ff 100644 --- a/behavior_metrics/utils/controller_carla.py +++ b/behavior_metrics/utils/controller_carla.py @@ -266,17 +266,16 @@ def record_metrics(self, metrics_record_dir_path, world_counter=None, brain_coun self.experiment_metrics['experiment_model'] = self.pilot.configuration.experiment_model[brain_counter] else: self.experiment_metrics['experiment_model'] = self.pilot.configuration.experiment_model + if hasattr(self.pilot.configuration, 'experiment_name'): self.experiment_metrics['experiment_name'] = self.pilot.configuration.experiment_name - if brain_counter is not None: - self.experiment_metrics['experiment_model'] = self.pilot.configuration.experiment_model[brain_counter] - else: - self.experiment_metrics['experiment_model'] = self.pilot.configuration.experiment_model + if hasattr(self.pilot.configuration, 'experiment_name'): self.experiment_metrics['experiment_name'] = self.pilot.configuration.experiment_name self.experiment_metrics['experiment_description'] = self.pilot.configuration.experiment_description self.experiment_metrics['experiment_timeout'] = self.pilot.configuration.experiment_timeouts[world_counter] self.experiment_metrics['experiment_repetition'] = repetition_counter + self.metrics_record_dir_path = metrics_record_dir_path os.mkdir(self.metrics_record_dir_path + self.time_str) @@ -330,13 +329,21 @@ def stop_recording_metrics(self): self.experiment_metrics['gpu_mean_inference_time'] = sum(self.pilot.brains.active_brain.inference_times) / len(self.pilot.brains.active_brain.inference_times) self.experiment_metrics['gpu_inference_frequency'] = 1 / self.experiment_metrics['gpu_mean_inference_time'] self.experiment_metrics['gpu_inference'] = self.pilot.brains.active_brain.gpu_inference + else: + self.experiment_metrics['gpu_mean_inference_time'] = 0 + self.experiment_metrics['gpu_inference_frequency'] = 0 + self.experiment_metrics['gpu_inference'] = 0 if hasattr(self.pilot.brains.active_brain, 'bird_eye_view_images'): - self.experiment_metrics['brain_iterations_simulated_time'] = len(self.pilot.brain_iterations_simulated_time) self.experiment_metrics['bird_eye_view_images'] = self.pilot.brains.active_brain.bird_eye_view_images self.experiment_metrics['bird_eye_view_unique_images'] = self.pilot.brains.active_brain.bird_eye_view_unique_images self.experiment_metrics['bird_eye_view_unique_images_percentage'] = self.experiment_metrics['bird_eye_view_unique_images'] / self.experiment_metrics['bird_eye_view_images'] + else: + self.experiment_metrics['bird_eye_view_images'] = 0 + self.experiment_metrics['bird_eye_view_unique_images'] = 0 + self.experiment_metrics['bird_eye_view_unique_images_percentage'] = 0 + self.experiment_metrics['brain_iterations_simulated_time'] = len(self.pilot.brain_iterations_simulated_time) self.experiment_metrics['mean_brain_iterations_real_time'] = mean_brain_iterations_real_time self.experiment_metrics['brain_iterations_frequency_real_time'] = brain_iterations_frequency_real_time self.experiment_metrics['target_brain_iterations_real_time'] = target_brain_iterations_real_time From bd8948fd1baffe44d9c7f5b24e7f23b1156d7801 Mon Sep 17 00:00:00 2001 From: sergiopaniego Date: Tue, 3 Oct 2023 16:41:51 +0200 Subject: [PATCH 10/12] Updated GUI stats wind --- behavior_metrics/ui/gui/views/stats_window.py | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/behavior_metrics/ui/gui/views/stats_window.py b/behavior_metrics/ui/gui/views/stats_window.py index bf2c2a8c..cfcb5c58 100644 --- a/behavior_metrics/ui/gui/views/stats_window.py +++ b/behavior_metrics/ui/gui/views/stats_window.py @@ -128,7 +128,16 @@ def __init__(self, parent=None, controller=None): self.layout.addWidget(self.suddenness_distance_speed_label) self.suddenness_distance_speed_per_km_label = QLabel("Suddenness distance speed per km -> " + str(self.controller.experiment_metrics['suddenness_distance_speed_per_km'])) self.layout.addWidget(self.suddenness_distance_speed_per_km_label) - if hasattr(self.controller.experiment_metrics, 'dangerous_distance_pct_km'): + print('LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL') + print() + print() + print() + print(self.controller.experiment_metrics) + print() + print() + print() + print('LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL') + if 'dangerous_distance_pct_km' in self.controller.experiment_metrics: self.dangerous_distance_pct_km = QLabel("Percentage of dangerous distance per km -> " + str(self.controller.experiment_metrics['dangerous_distance_pct_km'])) self.layout.addWidget(self.dangerous_distance_pct_km) self.close_distance_pct_km = QLabel("Percentage of close distance per km -> " + str(self.controller.experiment_metrics['close_distance_pct_km'])) From 9eef3aec910a5b545d40147583ec605a08bfc8e9 Mon Sep 17 00:00:00 2001 From: sergiopaniego Date: Tue, 3 Oct 2023 16:46:36 +0200 Subject: [PATCH 11/12] Removed log comment --- behavior_metrics/ui/gui/views/stats_window.py | 9 --------- 1 file changed, 9 deletions(-) diff --git a/behavior_metrics/ui/gui/views/stats_window.py b/behavior_metrics/ui/gui/views/stats_window.py index cfcb5c58..1c6ad940 100644 --- a/behavior_metrics/ui/gui/views/stats_window.py +++ b/behavior_metrics/ui/gui/views/stats_window.py @@ -128,15 +128,6 @@ def __init__(self, parent=None, controller=None): self.layout.addWidget(self.suddenness_distance_speed_label) self.suddenness_distance_speed_per_km_label = QLabel("Suddenness distance speed per km -> " + str(self.controller.experiment_metrics['suddenness_distance_speed_per_km'])) self.layout.addWidget(self.suddenness_distance_speed_per_km_label) - print('LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL') - print() - print() - print() - print(self.controller.experiment_metrics) - print() - print() - print() - print('LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL') if 'dangerous_distance_pct_km' in self.controller.experiment_metrics: self.dangerous_distance_pct_km = QLabel("Percentage of dangerous distance per km -> " + str(self.controller.experiment_metrics['dangerous_distance_pct_km'])) self.layout.addWidget(self.dangerous_distance_pct_km) From 2a44f277c3b18b5220678b1c66af0d02f2a7030c Mon Sep 17 00:00:00 2001 From: sergiopaniego Date: Tue, 3 Oct 2023 16:55:26 +0200 Subject: [PATCH 12/12] Updated configuration file --- .../configs/CARLA/default_carla_subjective_vision.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml index 4a372d0a..e9df8537 100644 --- a/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml +++ b/behavior_metrics/configs/CARLA/default_carla_subjective_vision.yml @@ -47,7 +47,7 @@ Behaviors: ImageTranform: '' Type: 'CARLA' Simulation: - World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_npc_low.launch + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_single_ad_low.launch RandomSpawnPoint: False MultiCar: True NumberOfVehicle: 0

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