Add files using upload-large-folder tool

.gitattributes

@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+__pycache__/Changed_MLR_All_Strategies.cpython-312.pyc filter=lfs diff=lfs merge=lfs -text

requirements_runpod.txt

@@ -0,0 +1,13 @@
+# Use this with a RunPod PyTorch image that already includes torch/torchvision + CUDA.
+# This avoids wasting setup time reinstalling large GPU wheels.
+
+numpy>=1.24.0
+scipy>=1.10.0
+pillow>=10.0.0
+tqdm>=4.66.0
+matplotlib>=3.8.0
+pandas>=2.2.0
+openpyxl>=3.1.0
+optuna>=3.6.0
+segmentation-models-pytorch>=0.5.0
+timm>=1.0.0

runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/exports/aggregated_metrics_by_percent_strategy.csv

@@ -0,0 +1,2 @@
+biou_mean,biou_std,biou_within_run_std_mean,dataset_percent,dice_mean,dice_std,dice_within_run_std_mean,hd95_mean,hd95_std,hd95_within_run_std_mean,iou_mean,iou_std,iou_within_run_std_mean,n_runs,ppv_mean,ppv_std,ppv_within_run_std_mean,sen_mean,sen_std,sen_within_run_std_mean,strategy
+0.11851169168949127,0.0,0.11075872927904129,15,0.6919469833374023,0.0,0.3070889115333557,inf,nan,,0.5996636748313904,0.0,0.3050761818885803,1,0.7501575350761414,0.0,0.3167218565940857,0.7228458523750305,0.0,0.29963552951812744,3

runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/exports/aggregated_metrics_by_percent_strategy.json

@@ -0,0 +1,25 @@
+[
+  {
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+    "biou_std": 0.0,
+    "biou_within_run_std_mean": 0.11075872927904129,
+    "dataset_percent": 15,
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+    "dice_std": 0.0,
+    "dice_within_run_std_mean": 0.3070889115333557,
+    "hd95_mean": Infinity,
+    "hd95_std": NaN,
+    "hd95_within_run_std_mean": null,
+    "iou_mean": 0.5996636748313904,
+    "iou_std": 0.0,
+    "iou_within_run_std_mean": 0.3050761818885803,
+    "n_runs": 1,
+    "ppv_mean": 0.7501575350761414,
+    "ppv_std": 0.0,
+    "ppv_within_run_std_mean": 0.3167218565940857,
+    "sen_mean": 0.7228458523750305,
+    "sen_std": 0.0,
+    "sen_within_run_std_mean": 0.29963552951812744,
+    "strategy": 3
+  }
+]

runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/exports/raw_run_metrics.csv

@@ -0,0 +1,2 @@
+biou_mean,biou_std,dataset_percent,dice_mean,dice_std,evaluation_path,hd95_mean,hd95_std,iou_mean,iou_std,ppv_mean,ppv_std,run_dir,sen_mean,sen_std,split_manifest_path,split_repeat_index,strategy,subset_manifest_path,subset_repeat_index
+0.11851169168949127,0.11075872927904129,15,0.6919469833374023,0.3070889115333557,/workspace/runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/strategy_3/final/evaluation.json,inf,,0.5996636748313904,0.3050761818885803,0.7501575350761414,0.3167218565940857,/workspace/runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/strategy_3/final,0.7228458523750305,0.29963552951812744,/workspace/runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/manifests/splits/split_001.json,1,3,/workspace/runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/manifests/subsets/split_001_pct_015_repeat_01.json,1

runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/exports/raw_run_metrics.json

@@ -0,0 +1,24 @@
+[
+  {
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+    "biou_std": 0.11075872927904129,
+    "dataset_percent": 15,
+    "dice_mean": 0.6919469833374023,
+    "dice_std": 0.3070889115333557,
+    "evaluation_path": "/workspace/runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/strategy_3/final/evaluation.json",
+    "hd95_mean": Infinity,
+    "hd95_std": null,
+    "iou_mean": 0.5996636748313904,
+    "iou_std": 0.3050761818885803,
+    "ppv_mean": 0.7501575350761414,
+    "ppv_std": 0.3167218565940857,
+    "run_dir": "/workspace/runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/strategy_3/final",
+    "sen_mean": 0.7228458523750305,
+    "sen_std": 0.29963552951812744,
+    "split_manifest_path": "/workspace/runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/manifests/splits/split_001.json",
+    "split_repeat_index": 1,
+    "strategy": 3,
+    "subset_manifest_path": "/workspace/runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/manifests/subsets/split_001_pct_015_repeat_01.json",
+    "subset_repeat_index": 1
+  }
+]

runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/norm_stats_BUSI_with_classes_stratified_80_10_10_015pct_repeat01.json

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runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/strategy_3/final/evaluation.json

@@ -0,0 +1,620 @@
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+}

runs/EfficientNetB0_BIOU_New_Code/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/strategy_3/final/low_iou_samples.csv

@@ -0,0 +1,6 @@
+sample_id
+BUSI_0273_B
+BUSI_0163_M
+BUSI_0315_B
+BUSI_0157_M
+BUSI_0256_B

runs/EfficientNetB0_BIOU_New_Code_OPTUNA/repeated_holdout/stratified_holdout_v1/exports/aggregated_metrics_by_percent_strategy.json

@@ -0,0 +1 @@
+[]

runs/EfficientNetB0_BIOU_New_Code_OPTUNA/repeated_holdout/stratified_holdout_v1/exports/raw_run_metrics.json

@@ -0,0 +1 @@
+[]

runs/EfficientNetB0_BIOU_New_Code_OPTUNA/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/norm_stats_BUSI_with_classes_stratified_80_10_10_015pct_repeat01.json

@@ -0,0 +1,85 @@
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runs/EfficientNetB0_BIOU_New_Code_OPTUNA/repeated_holdout/stratified_holdout_v1/split_001/pct_015/repeat_01/strategy_3/study/best_params.json

@@ -0,0 +1,31 @@
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