【课程设计】使用TensorRT部署RT-DETR目标检测算法python源码.zip

# RT-DETR Deploy with ONNX and TensorRT  base on project https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rtdetr **not need NMS not need Anchors and soeasy post process** ## 1.Clone project ```shell git clone https://github.com/PaddlePaddle/PaddleDetection.git ``` ## 2.Export paddlepaddle model ```shell cd PaddleDetection/ python tools/export_model.py -c configs/rtdetr/rtdetr_hgnetv2_l_6x_coco.yml -o weights=https://bj.bcebos.com/v1/paddledet/models/rtdetr_hgnetv2_l_6x_coco.pdparams trt=True --output_dir=output_inference ``` note: need paddlepaddle python package >= 2.4.0 ## 3.Convert paddlepaddle model to onnx model ```shell paddle2onnx --model_dir=./output_inference/rtdetr_hgnetv2_l_6x_coco/ --model_filename model.pdmodel --params_filename model.pdiparams --opset_version 16 --save_file rtdetr_hgnetv2_l_6x_coco.onnx ``` ## 4.Simplify onnx model ```shell onnxsim rtdetr_hgnetv2_l_6x_coco.onnx rtdetr_hgnetv2_l_6x_coco-sim.onnx --overwrite-input-shape im_shape:1,2 image:1,3,640,640 scale_factor:1,2 ```   ## 5.ONNX infer with simplified model ```shell python 1.onnx_run_original_onnx_post_process.py ``` and will generate a result.jpg ## 6.Modify onnx model to only one input simplified model has three inputs (im_shape, image, scale_factor),but we want only one input of model. use script modify onnx model ```shell python modify_onnx.py -i rtdetr_hgnetv2_l_6x_coco-sim.onnx -o rtdetr_hgnetv2_l_6x_coco-modify.onnx ```   ## 7.ONNX infer with modified model ```shell python 2.onnx_run_modify_onnx_no_post_process.py ``` ## 8.Generate TensorRT engine for supporting `GatherND` and `GridSample` op need TensorRT version >= 8.5 * GatherND TensorRT >= 8.4 * GridSample TensorRT >= 8.5 ```shell trtexec --onnx=rtdetr_hgnetv2_l_6x_coco-modify.onnx --saveEngine=rtdetr_hgnetv2_l_6x_coco-modify-fp32.engine ```