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  1. tutorial.ipynb +31 -7
tutorial.ipynb CHANGED
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@@ -564,7 +580,7 @@
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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",
@@ -585,7 +601,15 @@
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  "\n",
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  "`detect.py` runs YOLOv5 inference on a variety of sources, downloading models automatically from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases), and saving results to `runs/detect`. Example inference sources are:\n",
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  "\n",
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- "<img align=\"left\" src=\"https://user-images.githubusercontent.com/26833433/114307955-5c7e4e80-9ae2-11eb-9f50-a90e39bee53f.png\" width=\"900\"> "
 
 
 
 
 
 
 
 
589
  ]
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  },
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  {
@@ -601,7 +625,7 @@
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  "!python detect.py --weights yolov5s.pt --img 640 --conf 0.25 --source data/images/\n",
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  "Image(filename='runs/detect/exp/zidane.jpg', width=600)"
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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",
@@ -675,7 +699,7 @@
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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 ../datasets && rm tmp.zip"
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  ],
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- "execution_count": 10,
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  "outputs": [
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  {
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  "output_type": "display_data",
@@ -715,7 +739,7 @@
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  "# Run YOLOv5x on COCO val2017\n",
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  "!python val.py --weights yolov5x.pt --data coco.yaml --img 640 --iou 0.65 --half"
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  ],
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- "execution_count": 11,
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  "outputs": [
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  {
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  "output_type": "stream",
@@ -839,7 +863,7 @@
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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": 12,
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  "outputs": [
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  {
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  "output_type": "display_data",
@@ -917,7 +941,7 @@
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  "# Train YOLOv5s on COCO128 for 3 epochs\n",
918
  "!python train.py --img 640 --batch 16 --epochs 3 --data coco128.yaml --weights yolov5s.pt --cache"
919
  ],
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- "execution_count": 13,
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  "outputs": [
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  {
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  "output_type": "stream",
 
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+ "model_module_version": "1.5.0",
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  "_model_name": "DescriptionStyleModel",
 
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  "state": {
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  "_view_name": "LayoutView",
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  "grid_template_rows": null,
 
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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'})\")"
582
  ],
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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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  "\n",
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  "`detect.py` runs YOLOv5 inference on a variety of sources, downloading models automatically from the [latest YOLOv5 release](https://github.com/ultralytics/yolov5/releases), and saving results to `runs/detect`. Example inference sources are:\n",
603
  "\n",
604
+ "```shell\n",
605
+ "python detect.py --source 0 # webcam\n",
606
+ " file.jpg # image \n",
607
+ " file.mp4 # video\n",
608
+ " path/ # directory\n",
609
+ " path/*.jpg # glob\n",
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+ " 'https://youtu.be/NUsoVlDFqZg' # YouTube\n",
611
+ " 'rtsp://example.com/media.mp4' # RTSP, RTMP, HTTP stream\n",
612
+ "```"
613
  ]
614
  },
615
  {
 
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  "!python detect.py --weights yolov5s.pt --img 640 --conf 0.25 --source data/images/\n",
626
  "Image(filename='runs/detect/exp/zidane.jpg', width=600)"
627
  ],
628
+ "execution_count": null,
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  "outputs": [
630
  {
631
  "output_type": "stream",
 
699
  "torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v1.0/coco2017val.zip', 'tmp.zip')\n",
700
  "!unzip -q tmp.zip -d ../datasets && rm tmp.zip"
701
  ],
702
+ "execution_count": null,
703
  "outputs": [
704
  {
705
  "output_type": "display_data",
 
739
  "# Run YOLOv5x on COCO val2017\n",
740
  "!python val.py --weights yolov5x.pt --data coco.yaml --img 640 --iou 0.65 --half"
741
  ],
742
+ "execution_count": null,
743
  "outputs": [
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  {
745
  "output_type": "stream",
 
863
  "torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip', 'tmp.zip')\n",
864
  "!unzip -q tmp.zip -d ../ && rm tmp.zip"
865
  ],
866
+ "execution_count": null,
867
  "outputs": [
868
  {
869
  "output_type": "display_data",
 
941
  "# Train YOLOv5s on COCO128 for 3 epochs\n",
942
  "!python train.py --img 640 --batch 16 --epochs 3 --data coco128.yaml --weights yolov5s.pt --cache"
943
  ],
944
+ "execution_count": null,
945
  "outputs": [
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  {
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  "output_type": "stream",