diff --git a/configs/rtmdet/README.md b/configs/rtmdet/README.md index 5ea574dd78b..4574dd613c1 100644 --- a/configs/rtmdet/README.md +++ b/configs/rtmdet/README.md @@ -27,6 +27,7 @@ In this paper, we aim to design an efficient real-time object detector that exce | RTMDet-m | 640 | 49.4 | 24.71 | 39.27 | 1.62 | 6.41 | [config](./rtmdet_m_8xb32-300e_coco.py) | [model](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_m_8xb32-300e_coco/rtmdet_m_8xb32-300e_coco_20220719_112220-229f527c.pth) \| [log](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_m_8xb32-300e_coco/rtmdet_m_8xb32-300e_coco_20220719_112220.log.json) | | RTMDet-l | 640 | 51.5 | 52.3 | 80.23 | 2.44 | 10.32 | [config](./rtmdet_l_8xb32-300e_coco.py) | [model](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_l_8xb32-300e_coco/rtmdet_l_8xb32-300e_coco_20220719_112030-5a0be7c4.pth) \| [log](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_l_8xb32-300e_coco/rtmdet_l_8xb32-300e_coco_20220719_112030.log.json) | | RTMDet-x | 640 | 52.8 | 94.86 | 141.67 | 3.10 | 18.80 | [config](./rtmdet_x_8xb32-300e_coco.py) | [model](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_x_8xb32-300e_coco/rtmdet_x_8xb32-300e_coco_20220715_230555-cc79b9ae.pth) \| [log](https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_x_8xb32-300e_coco/rtmdet_x_8xb32-300e_coco_20220715_230555.log.json) | +| RTMDet-x-P6 | 1280 | 54.9 | | | | | [config](./rtmdet_x_p6_4xb8-300e_coco.py) | [model](https://github.com/orange0-jp/orange-weights/releases/download/v0.1.0rtmdet-p6/rtmdet_x_p6_4xb8-300e_coco-bf32be58.pth) | **Note**: diff --git a/configs/rtmdet/metafile.yml b/configs/rtmdet/metafile.yml index c4e8c9b796c..7dc72e130be 100644 --- a/configs/rtmdet/metafile.yml +++ b/configs/rtmdet/metafile.yml @@ -90,6 +90,20 @@ Models: box AP: 52.6 Weights: https://download.openmmlab.com/mmdetection/v3.0/rtmdet/rtmdet_x_8xb32-300e_coco/rtmdet_x_8xb32-300e_coco_20220715_230555-cc79b9ae.pth + - Name: rtmdet_x_p6_4xb8-300e_coco + Alias: + - rtmdet-x_p6 + In Collection: RTMDet + Config: configs/rtmdet/rtmdet_x_p6_4xb8-300e_coco.py + Metadata: + Epochs: 300 + Results: + - Task: Object Detection + Dataset: COCO + Metrics: + box AP: 54.9 + Weights: https://github.com/orange0-jp/orange-weights/releases/download/v0.1.0rtmdet-p6/rtmdet_x_p6_4xb8-300e_coco-bf32be58.pth + - Name: rtmdet-ins_tiny_8xb32-300e_coco Alias: - rtmdet-ins-t diff --git a/configs/rtmdet/rtmdet_x_p6_4xb8-300e_coco.py b/configs/rtmdet/rtmdet_x_p6_4xb8-300e_coco.py new file mode 100644 index 00000000000..d1bb7fa6a78 --- /dev/null +++ b/configs/rtmdet/rtmdet_x_p6_4xb8-300e_coco.py @@ -0,0 +1,132 @@ +_base_ = './rtmdet_x_8xb32-300e_coco.py' + +model = dict( + backbone=dict(arch='P6', out_indices=(2, 3, 4, 5)), + neck=dict(in_channels=[320, 640, 960, 1280]), + bbox_head=dict( + anchor_generator=dict( + type='MlvlPointGenerator', offset=0, strides=[8, 16, 32, 64]))) + +train_pipeline = [ + dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}), + dict(type='LoadAnnotations', with_bbox=True), + dict(type='CachedMosaic', img_scale=(1280, 1280), pad_val=114.0), + dict( + type='RandomResize', + scale=(2560, 2560), + ratio_range=(0.1, 2.0), + keep_ratio=True), + dict(type='RandomCrop', crop_size=(1280, 1280)), + dict(type='YOLOXHSVRandomAug'), + dict(type='RandomFlip', prob=0.5), + dict(type='Pad', size=(1280, 1280), pad_val=dict(img=(114, 114, 114))), + dict( + type='CachedMixUp', + img_scale=(1280, 1280), + ratio_range=(1.0, 1.0), + max_cached_images=20, + pad_val=(114, 114, 114)), + dict(type='PackDetInputs') +] + +train_pipeline_stage2 = [ + dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}), + dict(type='LoadAnnotations', with_bbox=True), + dict( + type='RandomResize', + scale=(1280, 1280), + ratio_range=(0.1, 2.0), + keep_ratio=True), + dict(type='RandomCrop', crop_size=(1280, 1280)), + dict(type='YOLOXHSVRandomAug'), + dict(type='RandomFlip', prob=0.5), + dict(type='Pad', size=(1280, 1280), pad_val=dict(img=(114, 114, 114))), + dict(type='PackDetInputs') +] + +test_pipeline = [ + dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}), + dict(type='Resize', scale=(1280, 1280), keep_ratio=True), + dict(type='Pad', size=(1280, 1280), pad_val=dict(img=(114, 114, 114))), + dict(type='LoadAnnotations', with_bbox=True), + dict( + type='PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'scale_factor')) +] + +train_dataloader = dict( + batch_size=8, num_workers=20, dataset=dict(pipeline=train_pipeline)) +val_dataloader = dict( + batch_size=5, num_workers=20, dataset=dict(pipeline=test_pipeline)) +test_dataloader = val_dataloader + +max_epochs = 300 +stage2_num_epochs = 20 + +base_lr = 0.004 * 32 / 256 +optim_wrapper = dict(optimizer=dict(lr=base_lr)) + +param_scheduler = [ + dict( + type='LinearLR', + start_factor=1.0e-5, + by_epoch=False, + begin=0, + end=1000), + dict( + # use cosine lr from 150 to 300 epoch + type='CosineAnnealingLR', + eta_min=base_lr * 0.05, + begin=max_epochs // 2, + end=max_epochs, + T_max=max_epochs // 2, + by_epoch=True, + convert_to_iter_based=True), +] + +custom_hooks = [ + dict( + type='EMAHook', + ema_type='ExpMomentumEMA', + momentum=0.0002, + update_buffers=True, + priority=49), + dict( + type='PipelineSwitchHook', + switch_epoch=max_epochs - stage2_num_epochs, + switch_pipeline=train_pipeline_stage2) +] + +img_scales = [(1280, 1280), (640, 640), (1920, 1920)] +tta_pipeline = [ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='TestTimeAug', + transforms=[ + [ + dict(type='Resize', scale=s, keep_ratio=True) + for s in img_scales + ], + [ + # ``RandomFlip`` must be placed before ``Pad``, otherwise + # bounding box coordinates after flipping cannot be + # recovered correctly. + dict(type='RandomFlip', prob=1.), + dict(type='RandomFlip', prob=0.) + ], + [ + dict( + type='Pad', + size=(1920, 1920), + pad_val=dict(img=(114, 114, 114))), + ], + [dict(type='LoadAnnotations', with_bbox=True)], + [ + dict( + type='PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'scale_factor', 'flip', 'flip_direction')) + ] + ]) +]