{ "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 }