Add YOLOv7 support

docs/PPYOLOE.md

@@ -74,7 +74,7 @@ Open the `DeepStream-Yolo` folder and compile the lib
 
 ##
 
-### Edit the config_infer_primary_yoloV5 file
+### Edit the config_infer_primary_ppyoloe file
 
 Edit the `config_infer_primary_ppyoloe.txt` file according to your model (example for PP-YOLOE-s)
 
@@ -97,7 +97,7 @@ offsets=123.675;116.28;103.53
 
 ##
 
-### Edit the deepstream_app_config.txt file
+### Edit the deepstream_app_config file
 
 ```
 ...

docs/YOLOR.md

@@ -2,7 +2,7 @@
 
 **NOTE**: You need to use the main branch of the YOLOR repo to convert the model.
 
-**NOTE**: The cfg is required.
+**NOTE**: The cfg file is required.
 
 * [Convert model](#convert-model)
 * [Compile the lib](#compile-the-lib)
@@ -92,7 +92,7 @@ model-file=yolor_csp.wts
 
 ##
 
-### Edit the deepstream_app_config.txt file
+### Edit the deepstream_app_config file
 
 ```
 ...

docs/YOLOv5.md

@@ -2,7 +2,7 @@
 
 **NOTE**: You can use the main branch of the YOLOv5 repo to convert all model versions.
 
-**NOTE**: The yaml is not required.
+**NOTE**: The yaml file is not required.
 
 * [Convert model](#convert-model)
 * [Compile the lib](#compile-the-lib)
@@ -117,7 +117,7 @@ model-file=yolov5s.wts
 
 ##
 
-### Edit the deepstream_app_config.txt file
+### Edit the deepstream_app_config file
 
 ```
 ...

docs/YOLOv7.md

@@ -0,0 +1,133 @@
+# YOLOv7 usage
+
+**NOTE**: The yaml file is not required.
+
+* [Convert model](#convert-model)
+* [Compile the lib](#compile-the-lib)
+* [Edit the config_infer_primary_yoloV7 file](#edit-the-config_infer_primary_yolov7-file)
+* [Edit the deepstream_app_config file](#edit-the-deepstream_app_config-file)
+* [Testing the model](#testing-the-model)
+
+##
+
+### Convert model
+
+#### 1. Download the YOLOv7 repo and install the requirements
+
+```
+git clone https://github.com/WongKinYiu/yolov7.git
+cd yolov7
+pip3 install -r requirements.txt
+```
+
+**NOTE**: It is recommended to use Python virtualenv.
+
+#### 2. Copy conversor
+
+Copy the `gen_wts_yoloV7.py` file from `DeepStream-Yolo/utils` directory to the `yolov7` folder.
+
+#### 3. Download the model
+
+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
+```
+
+**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.
+
+#### 4. Convert model
+
+Generate the `cfg` and `wts` files (example for YOLOv7)
+
+```
+python3 gen_wts_yoloV7.py -w yolov7.pt
+```
+
+**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 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 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_yoloV7 file
+
+Edit the `config_infer_primary_yoloV7.txt` file according to your model (example for YOLOv7)
+
+```
+[property]
+...
+custom-network-config=yolov7.cfg
+model-file=yolov7.wts
+...
+```
+
+##
+
+### Edit the deepstream_app_config file
+
+```
+...
+[primary-gie]
+...
+config-file=config_infer_primary_yoloV7.txt
+```
+
+##
+
+### Testing the model
+
+```
+deepstream-app -c deepstream_app_config.txt
+```