Add YOLOv6 support

docs/YOLOX.md

@@ -15,7 +15,7 @@
 #### 1. Download the YOLOX repo and install the requirements
 
 ```
-git clone https://github.com/Megvii-BaseDetection/YOLOX
+git clone https://github.com/Megvii-BaseDetection/YOLOX.git
 cd YOLOX
 pip3 install -r requirements.txt
 ```
@@ -28,7 +28,7 @@ Copy the `gen_wts_yolox.py` file from `DeepStream-Yolo/utils` directory to the `
 
 #### 3. Download the model
 
-Download the `pth` file from [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX/releases) releases (example for YOLOX-s standard)
+Download the `pth` file from [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX/releases/) releases (example for YOLOX-s standard)
 
 ```
 wget https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_s.pth

docs/YOLOv5.md

@@ -46,6 +46,12 @@ Generate the `cfg` and `wts` files (example for YOLOv5s)
 python3 gen_wts_yoloV5.py -w yolov5s.pt
 ```
 
+**NOTE**: To convert a P6 model
+
+```
+--p6
+```
+
 **NOTE**: To change the inference size (defaut: 640)
 
 ```

docs/YOLOv6.md

@@ -0,0 +1,145 @@
+# YOLOv6 usage
+
+**NOTE**: The yaml file is not required.
+
+* [Convert model](#convert-model)
+* [Compile the lib](#compile-the-lib)
+* [Edit the config_infer_primary_yoloV6 file](#edit-the-config_infer_primary_yolov6-file)
+* [Edit the deepstream_app_config file](#edit-the-deepstream_app_config-file)
+* [Testing the model](#testing-the-model)
+
+##
+
+### Convert model
+
+#### 1. Download the YOLOv6 repo and install the requirements
+
+```
+git clone https://github.com/meituan/YOLOv6.git
+cd YOLOv6
+pip3 install -r requirements.txt
+```
+
+**NOTE**: It is recommended to use Python virtualenv.
+
+#### 2. Copy conversor
+
+Copy the `gen_wts_yoloV6.py` file from `DeepStream-Yolo/utils` directory to the `YOLOv6` folder.
+
+#### 3. Download the model
+
+Download the `pt` file from [YOLOv6](https://github.com/meituan/YOLOv6/releases/) releases (example for YOLOv6-S 3.0)
+
+```
+wget https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6s.pt
+```
+
+**NOTE**: You can use your custom model, but it is important to keep the YOLO model reference (`yolov6_`) in you `cfg` and `weights`/`wts` filenames to generate the engine correctly.
+
+#### 4. Convert model
+
+Generate the `cfg` and `wts` files (example for YOLOv6-S 3.0)
+
+```
+python3 gen_wts_yoloV6.py -w yolov6s.pt
+```
+
+**NOTE**: To convert a P6 model
+
+```
+--p6
+```
+
+**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 `cfg` and `wts` files to the `DeepStream-Yolo` folder.
+
+##
+
+### Compile the lib
+
+Open the `DeepStream-Yolo` folder and compile the lib
+
+* 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 6.1.1 / 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_yoloV6 file
+
+Edit the `config_infer_primary_yoloV6.txt` file according to your model (example for YOLOv6-S 3.0)
+
+```
+[property]
+...
+custom-network-config=yolov6s.cfg
+model-file=yolov6s.wts
+...
+```
+
+##
+
+### Edit the deepstream_app_config file
+
+```
+...
+[primary-gie]
+...
+config-file=config_infer_primary_yoloV6.txt
+```
+
+##
+
+### Testing the model
+
+```
+deepstream-app -c deepstream_app_config.txt
+```

docs/YOLOv7.md

@@ -31,7 +31,7 @@ Copy the `gen_wts_yoloV7.py` file from `DeepStream-Yolo/utils` directory to the
 Download the `pt` file from [YOLOv7](https://github.com/WongKinYiu/yolov7/releases/) releases (example for YOLOv7)
 
 ```
-wget hhttps://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt
+wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt
 ```
 
 **NOTE**: You can use your custom model, but it is important to keep the YOLO model reference (`yolov7_`) in you `cfg` and `weights`/`wts` filenames to generate the engine correctly.
@@ -48,6 +48,12 @@ Generate the `cfg` and `wts` files (example for YOLOv7)
 python3 gen_wts_yoloV7.py -w yolov7.pt
 ```
 
+**NOTE**: To convert a P6 model
+
+```
+--p6
+```
+
 **NOTE**: To change the inference size (defaut: 640)
 
 ```