blakeblackshear.frigate/notebooks/YOLO_NAS_Pretrained_Export.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "rmuF9iKWTbdk"
},
"outputs": [],
"source": [
"! pip install -q super_gradients==3.7.1"
]
},
{
"cell_type": "code",
"source": [
"! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.10/dist-packages/super_gradients/training/pretrained_models.py\n",
"! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.10/dist-packages/super_gradients/training/utils/checkpoint_utils.py"
],
"metadata": {
"id": "NiRCt917KKcL"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "dTB0jy_NNSFz"
},
"outputs": [],
"source": [
"from super_gradients.common.object_names import Models\n",
"from super_gradients.conversion import DetectionOutputFormatMode\n",
"from super_gradients.training import models\n",
"\n",
"model = models.get(Models.YOLO_NAS_S, pretrained_weights=\"coco\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "GymUghyCNXem"
},
"outputs": [],
"source": [
"# export the model for compatibility with Frigate\n",
"\n",
"model.export(\"yolo_nas_s.onnx\",\n",
" output_predictions_format=DetectionOutputFormatMode.FLAT_FORMAT,\n",
" max_predictions_per_image=20,\n",
" confidence_threshold=0.4,\n",
" input_image_shape=(320,320),\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "uBhXV5g4Nh42"
},
"outputs": [],
"source": [
"from google.colab import files\n",
"\n",
"files.download('yolo_nas_s.onnx')"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}