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  1. tutorial.ipynb +8 -7
tutorial.ipynb CHANGED
@@ -523,10 +523,11 @@
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  {
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  "cell_type": "markdown",
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  "metadata": {
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- "id": "HvhYZrIZCEyo"
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  },
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  "source": [
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- "<img src=\"https://user-images.githubusercontent.com/26833433/98702494-b71c4e80-237a-11eb-87ed-17fcd6b3f066.jpg\">\n",
 
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  "\n",
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  "This is the **official YOLOv5 πŸš€ notebook** authored by **Ultralytics**, and is freely available for redistribution under the [GPL-3.0 license](https://choosealicense.com/licenses/gpl-3.0/). \n",
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  "For more information please visit https://github.com/ultralytics/yolov5 and https://ultralytics.com. Thank you!"
@@ -563,7 +564,7 @@
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  "clear_output()\n",
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  "print(f\"Setup complete. Using torch {torch.__version__} ({torch.cuda.get_device_properties(0).name 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",
@@ -681,7 +682,7 @@
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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",
@@ -721,7 +722,7 @@
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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 --half"
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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",
@@ -845,7 +846,7 @@
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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": 2,
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  "outputs": [
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  {
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  "output_type": "display_data",
@@ -923,7 +924,7 @@
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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 --cache"
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  ],
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- "execution_count": 9,
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  "outputs": [
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  {
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  "output_type": "stream",
 
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  {
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  "cell_type": "markdown",
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  "metadata": {
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+ "id": "t6MPjfT5NrKQ"
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  },
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  "source": [
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+ "<a align=\"left\" href=\"https://ultralytics.com/yolov5\" target=\"_blank\">\n",
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+ "<img src=\"https://github.com/ultralytics/yolov5/releases/download/v1.0/splash_horizontal.png\"></a>\n",
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  "\n",
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  "This is the **official YOLOv5 πŸš€ notebook** authored by **Ultralytics**, and is freely available for redistribution under the [GPL-3.0 license](https://choosealicense.com/licenses/gpl-3.0/). \n",
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  "For more information please visit https://github.com/ultralytics/yolov5 and https://ultralytics.com. Thank you!"
 
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  "clear_output()\n",
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  "print(f\"Setup complete. Using torch {torch.__version__} ({torch.cuda.get_device_properties(0).name 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 --half"
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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",
847
  "!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 --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",