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	* Adjust pre_nms predictions to increase performance * Update yolonas export and rocm inference times
		
			
				
	
	
		
			89 lines
		
	
	
		
			2.3 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			89 lines
		
	
	
		
			2.3 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
| {
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|   "cells": [
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|     {
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|       "cell_type": "code",
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|       "execution_count": null,
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|       "metadata": {
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|         "id": "rmuF9iKWTbdk"
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|       },
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|       "outputs": [],
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|       "source": [
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|         "! pip install -q git+https://github.com/Deci-AI/super-gradients.git"
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|       ]
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|     },
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|     {
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|       "cell_type": "code",
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|       "execution_count": null,
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|       "metadata": {
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|         "id": "NiRCt917KKcL"
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|       },
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|       "outputs": [],
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|       "source": [
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|         "! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.11/dist-packages/super_gradients/training/pretrained_models.py\n",
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|         "! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.11/dist-packages/super_gradients/training/utils/checkpoint_utils.py"
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|       ]
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|     },
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|     {
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|       "cell_type": "code",
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|       "execution_count": null,
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|       "metadata": {
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|         "id": "dTB0jy_NNSFz"
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|       },
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|       "outputs": [],
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|       "source": [
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|         "from super_gradients.common.object_names import Models\n",
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|         "from super_gradients.conversion import DetectionOutputFormatMode\n",
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|         "from super_gradients.training import models\n",
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|         "\n",
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|         "model = models.get(Models.YOLO_NAS_S, pretrained_weights=\"coco\")"
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|       ]
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|     },
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|     {
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|       "cell_type": "code",
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|       "execution_count": null,
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|       "metadata": {
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|         "id": "GymUghyCNXem"
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|       },
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|       "outputs": [],
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|       "source": [
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|         "# export the model for compatibility with Frigate\n",
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|         "\n",
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|         "model.export(\"yolo_nas_s.onnx\",\n",
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|         "             output_predictions_format=DetectionOutputFormatMode.FLAT_FORMAT,\n",
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|         "             max_predictions_per_image=20,\n",
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|         "             num_pre_nms_predictions=300,\n",
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|         "             confidence_threshold=0.4,\n",
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|         "             input_image_shape=(320,320),\n",
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|         "            )"
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|       ]
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|     },
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|     {
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|       "cell_type": "code",
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|       "execution_count": null,
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|       "metadata": {
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|         "id": "uBhXV5g4Nh42"
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|       },
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|       "outputs": [],
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|       "source": [
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|         "from google.colab import files\n",
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|         "\n",
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|         "files.download('yolo_nas_s.onnx')"
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|       ]
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|     }
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|   ],
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|   "metadata": {
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|     "colab": {
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|       "provenance": []
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|     },
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|     "kernelspec": {
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|       "display_name": "Python 3",
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|       "name": "python3"
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|     },
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|     "language_info": {
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|       "name": "python"
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|     }
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|   },
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|   "nbformat": 4,
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|   "nbformat_minor": 0
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| }
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