add new scripts

bluemindai · Feb 18, 2024 · ff52cd9 · ff52cd9
1 parent affd88c
commit ff52cd9
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Showing 6 changed files with 66 additions and 10 deletions.
diff --git a/nnunetv2/experiment_planning/experiment_planners/default_experiment_planner.py b/nnunetv2/experiment_planning/experiment_planners/default_experiment_planner.py
@@ -515,7 +515,7 @@ def plan_experiment(self):
             'inherits_from': '3d_fullres',
             'batch_size': 2,
             "spacing": [1.0, 1.0, 1.0],
-            "patch_size": [128, 192, 192],
+            "patch_size": [192, 192, 192],
             "UNet_base_num_features": 32,
             "n_conv_per_stage_encoder": [
                 1,
@@ -635,15 +635,15 @@ def plan_experiment(self):
         print(plans['configurations']['3d_fullres_mosaic_resenc'])
         print()
 
-        plans['configurations']["3d_fullres_mosaic_resenc_192x192x192_bs3_1mm"]= {
+        plans['configurations']["3d_fullres_mosaic_resenc_192x192x192_bs2_1mm"]= {
             "inherits_from": "3d_fullres_mosaic_resenc",
             "spacing": [1.0, 1.0, 1.0],
             "patch_size": [
                 192,
                 192,
                 192
             ],
-            "batch_size": 3
+            "batch_size": 2
         }
 
         print('3D fullres Mosaic ResEncUnet 192x192x192 bs3 1mm')

diff --git a/scripts/del_npy.ipynb b/scripts/del_npy.ipynb
@@ -19,6 +19,55 @@
     "        os.remove(file_path)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[1, 3, 4, 6, 6, 6]"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a = [\n",
+    "                1,\n",
+    "                3,\n",
+    "                4,\n",
+    "                6,\n",
+    "                6,\n",
+    "                6\n",
+    "            ]\n",
+    "\n",
+    "a"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "6"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(a)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

diff --git a/scripts/generate_json.ipynb b/scripts/generate_json.ipynb
@@ -11,22 +11,21 @@
     "from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_json\n",
     "import os\n",
     "\n",
-    "dataset = \"/media/eolika/49755d50-5426-4672-87cc-2d1a5a3747ad/nnUNet/nnUNet_raw/Dataset201_renal_vessels\"\n",
+    "dataset = \"/media/eolika/49755d50-5426-4672-87cc-2d1a5a3747ad/nnUNet/nnUNet_raw/Dataset909_acute_ischemic_stroke\"\n",
     "\n",
     "generate_dataset_json(output_folder=dataset,\n",
     "                      channel_names={0: \"CT\"},\n",
     "                      labels={\n",
     "                          \"background\": 0,\n",
-    "                          \"renal_artery\": 1,\n",
-    "                          \"renal_vein\": 2\n",
+    "                          \"acute_ischemic_stroke\": 1\n",
     "                        },\n",
     "                        num_training_cases=len(os.listdir(f'{dataset}/imagesTr')), \n",
     "                        file_ending='.nii.gz',\n",
     "                        dataset_name=dataset.split('/')[-1], \n",
     "                        reference='none',\n",
     "                        release='1.0.0',\n",
     "                        overwrite_image_reader_writer='NibabelIOWithReorient',\n",
-    "                        description=\"renal_vessels\")"
+    "                        description=\"acute_ischemic_stroke\")"
    ]
   },
   {

diff --git a/scripts/plot_prepocess.sh b/scripts/plot_prepocess.sh
@@ -0,0 +1,6 @@
+#!/bin/bash
+read -p "Enter dataset id : " id
+read -p "Enter train config (ex. 3d_fullres, 3d_fullres_mosaic_arch2, 3d_fullres_mosaic_resenc) : " conf
+read -p "Enter output path: " output
+
+nnUNetv2_plot_overlay_pngs -d $id -o $output -c $conf
diff --git a/scripts/preprocess_resenc.sh b/scripts/preprocess_resenc.sh
@@ -2,7 +2,7 @@
 
 echo "Prepare target dataset on pretrained set."
 read -p "Enter source dataset: " id
-read -p "Enter train config (ex. 3d_fullres, 3d_fullres_mosaic_resenc, 3d_fullres_mosaic_resenc_192x192x192_bs3_1mm): " conf
+read -p "Enter train config (ex. 3d_fullres, 3d_fullres_mosaic_resenc, 3d_fullres_mosaic_resenc_192x192x192_bs2_1mm): " conf
 read -p "Enter a number of processors to use: " np
 
 nnUNetv2_extract_fingerprint -d $id

diff --git a/scripts/train.sh b/scripts/train.sh
@@ -2,10 +2,12 @@
 
 echo "Train model from scratch. Be sure that you have already created the dataset.json file!"
 read -p "Enter dataset id: " id
-read -p "Enter train config (ex. 3d_fullres or custom 3d_fullres_mosaic, 3d_fullres_mosaic_resenc, 3d_fullres_mosaic_resenc_192x192x192_bs3_1mm config): " conf
+read -p "Enter train config (ex. 3d_fullres or custom 3d_fullres_mosaic, 3d_fullres_mosaic_resenc, 3d_fullres_mosaic_resenc_192x192x192_bs2_1mm config): " conf
 read -p "Enter train fold ([0-4] or all usually): " fold
 read -p "Enter trainer you would like to choose (nnUNetTrainer, nnUNetTrainerNoMirroring, nnUNetTrainer_Xepochs-where X could be in [100, 250, 2000, 4000, 8000], nnUNetTrainerDiceCELoss_noSmooth): " trainer
 
 
 echo "Launching the train..."
-nnUNetv2_train "$id" --c "$conf" "$fold" -tr "$trainer"
+nnUNetv2_train "$id" --c "$conf" "$fold" -tr "$trainer"
+
+# nnUNet_compile=T nnUNet_n_proc_DA=28 nnUNetv2_train 221 3d_fullres_mosaic_resenc_192x192x192_bs3_1mm 0 -num_gpus 8