ultralytics 8.0.133 add torchvision compatibility check (#3703)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
GitHub
@ -66,7 +66,7 @@
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"import ultralytics\n",
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"ultralytics.checks()"
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],
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"execution_count": 1,
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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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@ -102,7 +102,7 @@
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"# Run inference on an image with YOLOv8n\n",
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"!yolo predict model=yolov8n.pt source='https://ultralytics.com/images/zidane.jpg'"
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],
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"execution_count": 2,
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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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@ -169,7 +169,7 @@
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"# Validate YOLOv8n on COCO128 val\n",
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"!yolo val model=yolov8n.pt data=coco128.yaml"
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],
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"execution_count": 3,
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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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@ -293,7 +293,7 @@
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"# Train YOLOv8n on COCO128 for 3 epochs\n",
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"!yolo train model=yolov8n.pt data=coco128.yaml epochs=3 imgsz=640"
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],
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"execution_count": 4,
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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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@ -454,21 +454,21 @@
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"- 💡 ProTip: Export to [TensorRT](https://developer.nvidia.com/tensorrt) for up to 5x GPU speedup.\n",
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"\n",
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"\n",
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"| Format | `format=` | Model |\n",
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"|----------------------------------------------------------------------------|--------------------|---------------------------|\n",
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"| [PyTorch](https://pytorch.org/) | - | `yolov8n.pt` |\n",
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"| [TorchScript](https://pytorch.org/docs/stable/jit.html) | `torchscript` | `yolov8n.torchscript` |\n",
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"| [ONNX](https://onnx.ai/) | `onnx` | `yolov8n.onnx` |\n",
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"| [OpenVINO](https://docs.openvino.ai/latest/index.html) | `openvino` | `yolov8n_openvino_model/` |\n",
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"| [TensorRT](https://developer.nvidia.com/tensorrt) | `engine` | `yolov8n.engine` |\n",
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"| [CoreML](https://github.com/apple/coremltools) | `coreml` | `yolov8n.mlmodel` |\n",
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"| [TensorFlow SavedModel](https://www.tensorflow.org/guide/saved_model) | `saved_model` | `yolov8n_saved_model/` |\n",
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"| [TensorFlow GraphDef](https://www.tensorflow.org/api_docs/python/tf/Graph) | `pb` | `yolov8n.pb` |\n",
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"| [TensorFlow Lite](https://www.tensorflow.org/lite) | `tflite` | `yolov8n.tflite` |\n",
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"| [TensorFlow Edge TPU](https://coral.ai/docs/edgetpu/models-intro/) | `edgetpu` | `yolov8n_edgetpu.tflite` |\n",
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"| [TensorFlow.js](https://www.tensorflow.org/js) | `tfjs` | `yolov8n_web_model/` |\n",
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"| [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n_paddle_model/` |\n",
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"\n"
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"| Format | `format` Argument | Model |\n",
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"|----------------------------------------------------------------------------|-------------------|---------------------------|\n",
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"| [PyTorch](https://pytorch.org/) | - | `yolov8n.pt` |\n",
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"| [TorchScript](https://pytorch.org/docs/stable/jit.html) | `torchscript` | `yolov8n.torchscript` |\n",
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"| [ONNX](https://onnx.ai/) | `onnx` | `yolov8n.onnx` |\n",
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"| [OpenVINO](https://docs.openvino.ai/latest/index.html) | `openvino` | `yolov8n_openvino_model/` |\n",
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"| [TensorRT](https://developer.nvidia.com/tensorrt) | `engine` | `yolov8n.engine` |\n",
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"| [CoreML](https://github.com/apple/coremltools) | `coreml` | `yolov8n.mlmodel` |\n",
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"| [TensorFlow SavedModel](https://www.tensorflow.org/guide/saved_model) | `saved_model` | `yolov8n_saved_model/` |\n",
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"| [TensorFlow GraphDef](https://www.tensorflow.org/api_docs/python/tf/Graph) | `pb` | `yolov8n.pb` |\n",
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"| [TensorFlow Lite](https://www.tensorflow.org/lite) | `tflite` | `yolov8n.tflite` |\n",
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"| [TensorFlow Edge TPU](https://coral.ai/docs/edgetpu/models-intro/) | `edgetpu` | `yolov8n_edgetpu.tflite` |\n",
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"| [TensorFlow.js](https://www.tensorflow.org/js) | `tfjs` | `yolov8n_web_model/` |\n",
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"| [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n_paddle_model/` |\n",
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"| [NCNN](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n_ncnn_model/` |\n"
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],
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"metadata": {
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"id": "nPZZeNrLCQG6"
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@ -486,7 +486,7 @@
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"id": "CYIjW4igCjqD",
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"outputId": "fc41bf7a-0ea2-41a6-9ec5-dd0455af43bc"
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},
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"execution_count": 5,
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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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@ -533,7 +533,7 @@
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"results = model.train(data='coco128.yaml', epochs=3) # train the model\n",
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"results = model.val() # evaluate model performance on the validation set\n",
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"results = model('https://ultralytics.com/images/bus.jpg') # predict on an image\n",
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"success = model.export(format='onnx') # export the model to ONNX format"
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"results = model.export(format='onnx') # export the model to ONNX format"
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],
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"metadata": {
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"id": "bpF9-vS_DAaf"
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@ -677,9 +677,8 @@
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"cell_type": "code",
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"source": [
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"# Git clone and run tests on updates branch\n",
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"!git clone https://github.com/ultralytics/ultralytics -b updates\n",
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"%pip install -qe ultralytics\n",
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"!pytest ultralytics/tests"
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"!git clone https://github.com/ultralytics/ultralytics -b main\n",
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"%pip install -qe ultralytics"
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],
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"metadata": {
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"id": "uRKlwxSJdhd1"
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@ -687,6 +686,18 @@
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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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"source": [
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"# Run tests (Git clone only)\n",
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"!pytest ultralytics/tests"
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],
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"metadata": {
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"id": "GtPlh7mcCGZX"
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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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"source": [
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