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  1. tutorial.ipynb +18 -5
tutorial.ipynb CHANGED
@@ -563,7 +563,7 @@
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  "clear_output()\n",
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  "print('Setup complete. Using torch %s %s' % (torch.__version__, torch.cuda.get_device_properties(0) if torch.cuda.is_available() else 'CPU'))"
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  ],
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- "execution_count": 1,
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  "outputs": [
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  {
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  "output_type": "stream",
@@ -689,7 +689,7 @@
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  "torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v1.0/coco2017val.zip', 'tmp.zip')\n",
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  "!unzip -q tmp.zip -d ../ && rm tmp.zip"
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  ],
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- "execution_count": 2,
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  "outputs": [
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  {
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  "output_type": "display_data",
@@ -729,7 +729,7 @@
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  "# Run YOLOv5x on COCO val2017\n",
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  "!python test.py --weights yolov5x.pt --data coco.yaml --img 640 --iou 0.65"
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  ],
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- "execution_count": 3,
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  "outputs": [
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  {
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  "output_type": "stream",
@@ -853,7 +853,7 @@
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  "torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip', 'tmp.zip')\n",
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  "!unzip -q tmp.zip -d ../ && rm tmp.zip"
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  ],
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- "execution_count": 4,
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  "outputs": [
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  {
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  "output_type": "display_data",
@@ -930,7 +930,7 @@
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  "# Train YOLOv5s on COCO128 for 3 epochs\n",
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  "!python train.py --img 640 --batch 16 --epochs 3 --data coco128.yaml --weights yolov5s.pt --nosave --cache"
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  ],
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- "execution_count": 5,
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  "outputs": [
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  {
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  "output_type": "stream",
@@ -1222,6 +1222,19 @@
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  "execution_count": null,
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  "outputs": []
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  },
 
 
 
 
 
 
 
 
 
 
 
 
 
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  {
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  "cell_type": "code",
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  "metadata": {
 
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  "clear_output()\n",
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  "print('Setup complete. Using torch %s %s' % (torch.__version__, torch.cuda.get_device_properties(0) if torch.cuda.is_available() else 'CPU'))"
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  ],
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+ "execution_count": null,
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  "outputs": [
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  {
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  "output_type": "stream",
 
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  "torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v1.0/coco2017val.zip', 'tmp.zip')\n",
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  "!unzip -q tmp.zip -d ../ && rm tmp.zip"
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  ],
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+ "execution_count": null,
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  "outputs": [
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  {
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  "output_type": "display_data",
 
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  "# Run YOLOv5x on COCO val2017\n",
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  "!python test.py --weights yolov5x.pt --data coco.yaml --img 640 --iou 0.65"
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  ],
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+ "execution_count": null,
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  "outputs": [
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  {
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  "output_type": "stream",
 
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  "torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip', 'tmp.zip')\n",
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  "!unzip -q tmp.zip -d ../ && rm tmp.zip"
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  ],
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+ "execution_count": null,
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  "outputs": [
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  {
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  "output_type": "display_data",
 
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  "# Train YOLOv5s on COCO128 for 3 epochs\n",
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  "!python train.py --img 640 --batch 16 --epochs 3 --data coco128.yaml --weights yolov5s.pt --nosave --cache"
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  ],
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+ "execution_count": null,
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  "outputs": [
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  {
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  "output_type": "stream",
 
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  "execution_count": null,
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  "outputs": []
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  },
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+ {
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+ "cell_type": "code",
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+ "metadata": {
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+ "id": "RVRSOhEvUdb5"
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+ },
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+ "source": [
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+ "# Evolve\n",
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+ "!python train.py --img 640 --batch 64 --epochs 100 --data coco128.yaml --weights yolov5s.pt --cache --noautoanchor --evolve\n",
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+ "!d=runs/train/evolve && cp evolve.* $d && zip -r evolve.zip $d && gsutil mv evolve.zip gs://bucket # upload results (optional)"
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+ ],
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+ "execution_count": null,
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+ "outputs": []
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+ },
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  {
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  "cell_type": "code",
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  "metadata": {