Add RT-DETR Paddle

docs/RTDETR_Paddle.md

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+# RT-DETR Paddle usage
+
+**NOTE**: https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetr_paddle version.
+
+* [Convert model](#convert-model)
+* [Compile the lib](#compile-the-lib)
+* [Edit the config_infer_primary_rtdetr file](#edit-the-config_infer_primary_rtdetr-file)
+* [Edit the deepstream_app_config file](#edit-the-deepstream_app_config-file)
+* [Testing the model](#testing-the-model)
+
+##
+
+### Convert model
+
+#### 1. Download the PaddleDetection repo and install the requirements
+
+https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.7/docs/tutorials/INSTALL.md
+
+```
+git clone https://github.com/lyuwenyu/RT-DETR.git
+cd RT-DETR/rtdetr_paddle
+pip3 install -r requirements.txt
+pip3 install onnx onnxsim onnxruntime paddle2onnx
+```
+
+**NOTE**: It is recommended to use Python virtualenv.
+
+#### 2. Copy conversor
+
+Copy the `export_rtdetr_paddle.py` file from `DeepStream-Yolo/utils` directory to the `RT-DETR/rtdetr_paddle` folder.
+
+#### 3. Download the model
+
+Download the `pdparams` file from [RT-DETR Paddle](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetr_paddle) releases (example for RT-DETR-R50)
+
+```
+wget https://bj.bcebos.com/v1/paddledet/models/rtdetr_r50vd_6x_coco.pdparams
+```
+
+**NOTE**: You can use your custom model.
+
+#### 4. Convert model
+
+Generate the ONNX model file (example for RT-DETR-R50)
+
+```
+python3 export_rtdetr_paddle.py -w rtdetr_r50vd_6x_coco.pdparams -c configs/rtdetr/rtdetr_r50vd_6x_coco.yml --dynamic
+```
+
+**NOTE**: To simplify the ONNX model (DeepStream >= 6.0)
+
+```
+--simplify
+```
+
+**NOTE**: To use dynamic batch-size (DeepStream >= 6.1)
+
+```
+--dynamic
+```
+
+**NOTE**: To use static batch-size (example for batch-size = 4)
+
+```
+--batch 4
+```
+
+**NOTE**: If you are using the DeepStream 5.1, remove the `--dynamic` arg and use opset 12 or lower. The default opset is 16.
+
+```
+--opset 12
+```
+
+#### 5. Copy generated files
+
+Copy the generated ONNX model file and labels.txt file (if generated) to the `DeepStream-Yolo` folder.
+
+##
+
+### Compile the lib
+
+Open the `DeepStream-Yolo` folder and compile the lib
+
+* DeepStream 6.3 on x86 platform
+
+  ```
+  CUDA_VER=12.1 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+* DeepStream 6.2 on x86 platform
+
+  ```
+  CUDA_VER=11.8 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+* DeepStream 6.1.1 on x86 platform
+
+  ```
+  CUDA_VER=11.7 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+* DeepStream 6.1 on x86 platform
+
+  ```
+  CUDA_VER=11.6 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+* DeepStream 6.0.1 / 6.0 on x86 platform
+
+  ```
+  CUDA_VER=11.4 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+* DeepStream 5.1 on x86 platform
+
+  ```
+  CUDA_VER=11.1 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+* DeepStream 6.3 / 6.2 / 6.1.1 / 6.1 on Jetson platform
+
+  ```
+  CUDA_VER=11.4 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+* DeepStream 6.0.1 / 6.0 / 5.1 on Jetson platform
+
+  ```
+  CUDA_VER=10.2 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+##
+
+### Edit the config_infer_primary_rtdetr file
+
+Edit the `config_infer_primary_rtdetr.txt` file according to your model (example for RT-DETR-R50 with 80 classes)
+
+```
+[property]
+...
+onnx-file=rtdetr_r50vd_6x_coco.onnx
+...
+num-detected-classes=80
+...
+parse-bbox-func-name=NvDsInferParseYolo
+...
+```
+
+**NOTE**: The **RT-DETR** do not resize the input with padding. To get better accuracy, use
+
+```
+[property]
+...
+maintain-aspect-ratio=0
+...
+```
+
+##
+
+### Edit the deepstream_app_config file
+
+```
+...
+[primary-gie]
+...
+config-file=config_infer_primary_rtdetr.txt
+```
+
+##
+
+### Testing the model
+
+```
+deepstream-app -c deepstream_app_config.txt
+```
+
+**NOTE**: The TensorRT engine file may take a very long time to generate (sometimes more than 10 minutes).
+
+**NOTE**: For more information about custom models configuration (`batch-size`, `network-mode`, etc), please check the [`docs/customModels.md`](customModels.md) file.