Add DAMO-YOLO + Fixes

docs/DAMOYOLO.md

@@ -0,0 +1,158 @@
+# DAMO-YOLO usage
+
+* [Convert model](#convert-model)
+* [Compile the lib](#compile-the-lib)
+* [Edit the config_infer_primary_damoyolo file](#edit-the-config_infer_primary_damoyolo-file)
+* [Edit the deepstream_app_config file](#edit-the-deepstream_app_config-file)
+* [Testing the model](#testing-the-model)
+
+##
+
+### Convert model
+
+#### 1. Download the DAMO-YOLO repo and install the requirements
+
+```
+git clone https://github.com/tinyvision/DAMO-YOLO.git
+cd DAMO-YOLO
+pip3 install -r requirements.txt
+pip3 install onnx onnxsim onnxruntime
+```
+
+**NOTE**: It is recommended to use Python virtualenv.
+
+#### 2. Copy conversor
+
+Copy the `export_damoyolo.py` file from `DeepStream-Yolo/utils` directory to the `DAMO-YOLO` folder.
+
+#### 3. Download the model
+
+Download the `pth` file from [DAMO-YOLO](https://github.com/tinyvision/DAMO-YOLO) releases (example for DAMO-YOLO-S*)
+
+```
+wget https://idstcv.oss-cn-zhangjiakou.aliyuncs.com/DAMO-YOLO/release_model/clean_model_0317/damoyolo_tinynasL25_S_477.pth
+```
+
+**NOTE**: You can use your custom model.
+
+#### 4. Convert model
+
+Generate the ONNX model file (example for DAMO-YOLO-S*)
+
+```
+python3 export_damoyolo.py -w damoyolo_tinynasL25_S_477.pth -c configs/damoyolo_tinynasL25_S.py --simplify
+```
+
+**NOTE**: To change the inference size (defaut: 640)
+
+```
+-s SIZE
+--size SIZE
+-s HEIGHT WIDTH
+--size HEIGHT WIDTH
+```
+
+Example for 1280
+
+```
+-s 1280
+```
+
+or
+
+```
+-s 1280 1280
+```
+
+#### 5. Copy generated files
+
+Copy the generated ONNX model file to the `DeepStream-Yolo` folder.
+
+##
+
+### Compile the lib
+
+Open the `DeepStream-Yolo` folder and compile the lib
+
+* 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 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 on Jetson platform
+
+  ```
+  CUDA_VER=10.2 make -C nvdsinfer_custom_impl_Yolo
+  ```
+
+##
+
+### Edit the config_infer_primary_damoyolo file
+
+Edit the `config_infer_primary_damoyolo.txt` file according to your model (example for DAMO-YOLO-S* with 80 classes)
+
+```
+[property]
+...
+onnx-file=damoyolo_tinynasL25_S.onnx
+model-engine-file=damoyolo_tinynasL25_S.onnx_b1_gpu0_fp32.engine
+...
+num-detected-classes=80
+...
+parse-bbox-func-name=NvDsInferParseYoloE
+...
+```
+
+**NOTE**: The **DAMO-YOLO** do not resize the input with padding. To get better accuracy, use
+
+```
+maintain-aspect-ratio=0
+```
+
+##
+
+### Edit the deepstream_app_config file
+
+```
+...
+[primary-gie]
+...
+config-file=config_infer_primary_damoyolo.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.

docs/YOLONAS.md

@@ -30,7 +30,7 @@ Copy the `export_yolonas.py` file from `DeepStream-Yolo/utils` directory to the
 
 #### 3. Download the model
 
-Download the `pth` file from [YOLO-NAS](https://sghub.deci.ai/) website (example for YOLO-NAS S)
+Download the `pth` file from [YOLO-NAS](https://sghub.deci.ai/) releases (example for YOLO-NAS S)
 
 ```
 wget https://sghub.deci.ai/models/yolo_nas_s_coco.pth

docs/YOLOX.md

@@ -2,8 +2,6 @@
 
 **NOTE**: You can use the main branch of the YOLOX repo to convert all model versions.
 
-**NOTE**: The yaml file is not required.
-
 * [Convert model](#convert-model)
 * [Compile the lib](#compile-the-lib)
 * [Edit the config_infer_primary_yolox file](#edit-the-config_infer_primary_yolox-file)