yolo with runs.zip file exp 14 is the best weight

yolov3/data/scripts/download_weights.sh

@@ -1,22 +1,18 @@
 #!/bin/bash
 # YOLOv3 🚀 by Ultralytics, GPL-3.0 license
-# Download latest models from https://github.com/ultralytics/yolov5/releases
-# Example usage: bash data/scripts/download_weights.sh
+# Download latest models from https://github.com/ultralytics/yolov3/releases
+# Example usage: bash path/to/download_weights.sh
 # parent
-# └── yolov5
-#     ├── yolov5s.pt  ← downloads here
-#     ├── yolov5m.pt
+# └── yolov3
+#     ├── yolov3.pt  ← downloads here
+#     ├── yolov3-spp.pt
 #     └── ...
 
 python - <<EOF
 from utils.downloads import attempt_download
 
-p5 = list('nsmlx')  # P5 models
-p6 = [f'{x}6' for x in p5]  # P6 models
-cls = [f'{x}-cls' for x in p5]  # classification models
-seg = [f'{x}-seg' for x in p5]  # classification models
-
-for x in p5 + p6 + cls + seg:
-    attempt_download(f'weights/yolov5{x}.pt')
+models = ['yolov3', 'yolov3-spp', 'yolov3-tiny']
+for x in models:
+    attempt_download(f'{x}.pt')
 
 EOF

yolov3/data/scripts/get_coco.sh

@@ -3,54 +3,25 @@
 # Download COCO 2017 dataset http://cocodataset.org
 # Example usage: bash data/scripts/get_coco.sh
 # parent
-# ├── yolov5
+# ├── yolov3
 # └── datasets
 #     └── coco  ← downloads here
 
-# Arguments (optional) Usage: bash data/scripts/get_coco.sh --train --val --test --segments
-if [ "$#" -gt 0 ]; then
-  for opt in "$@"; do
-    case "${opt}" in
-    --train) train=true ;;
-    --val) val=true ;;
-    --test) test=true ;;
-    --segments) segments=true ;;
-    esac
-  done
-else
-  train=true
-  val=true
-  test=false
-  segments=false
-fi
-
 # Download/unzip labels
 d='../datasets' # unzip directory
 url=https://github.com/ultralytics/yolov5/releases/download/v1.0/
-if [ "$segments" == "true" ]; then
-  f='coco2017labels-segments.zip' # 168 MB
-else
-  f='coco2017labels.zip' # 46 MB
-fi
+f='coco2017labels.zip' # or 'coco2017labels-segments.zip', 68 MB
 echo 'Downloading' $url$f ' ...'
-curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &
+curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
 
 # Download/unzip images
 d='../datasets/coco/images' # unzip directory
 url=http://images.cocodataset.org/zips/
-if [ "$train" == "true" ]; then
-  f='train2017.zip' # 19G, 118k images
+f1='train2017.zip' # 19G, 118k images
+f2='val2017.zip'   # 1G, 5k images
+f3='test2017.zip'  # 7G, 41k images (optional)
+for f in $f1 $f2; do
   echo 'Downloading' $url$f '...'
-  curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &
-fi
-if [ "$val" == "true" ]; then
-  f='val2017.zip' # 1G, 5k images
-  echo 'Downloading' $url$f '...'
-  curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &
-fi
-if [ "$test" == "true" ]; then
-  f='test2017.zip' # 7G, 41k images (optional)
-  echo 'Downloading' $url$f '...'
-  curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &
-fi
+  curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
+done
 wait # finish background tasks

yolov3/data/scripts/get_coco128.sh

@@ -3,7 +3,7 @@
 # Download COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
 # Example usage: bash data/scripts/get_coco128.sh
 # parent
-# ├── yolov5
+# ├── yolov3
 # └── datasets
 #     └── coco128  ← downloads here
 
@@ -12,6 +12,6 @@ d='../datasets' # unzip directory
 url=https://github.com/ultralytics/yolov5/releases/download/v1.0/
 f='coco128.zip' # or 'coco128-segments.zip', 68 MB
 echo 'Downloading' $url$f ' ...'
-curl -L $url$f -o $f -# && unzip -q $f -d $d && rm $f &
+curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
 
 wait # finish background tasks