YOLOv7_Seg.md

YOLOv7-Seg usage

NOTE: The yaml file is not required.

• Convert model
• Compile the lib
• Edit the config_infer_primary_yoloV7_seg file

Convert model

1. Download the YOLOv7 repo and install the requirements

git clone -b u7 https://github.com/WongKinYiu/yolov7
cd yolov7/seg
pip3 install -r requirements.txt
pip3 install onnx onnxslim onnxruntime

NOTE: It is recommended to use Python virtualenv.

2. Copy conversor

Copy the export_yoloV7_seg.py file from DeepStream-Yolo-Seg/utils directory to the yolov7/seg folder.

3. Download the model

Download the pt file from YOLOv7 releases (example for YOLOv7-Seg)

wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-seg.pt

NOTE: You can use your custom model.

4. Convert model

Generate the ONNX model file (example for YOLOv7-Seg)

python3 export_yoloV7_seg.py -w yolov7-seg.pt --dynamic

NOTE: Minimum detection confidence threshold (example for conf-threshold = 0.25)

The minimum detection confidence threshold is configured in the ONNX exporter file. The pre-cluster-threshold should be >= the value used in the ONNX model.

--conf-threshold 0.25

NOTE: NMS IoU threshold (example for iou-threshold = 0.45)

--iou-threshold 0.45

NOTE: Maximum number of output detections (example for max-detections = 300)

--max-detections 300

NOTE: To convert a P6 model

--p6

NOTE: To change the inference size (defaut: 640 / 1280 for --p6 models)

-s SIZE
--size SIZE
-s HEIGHT WIDTH
--size HEIGHT WIDTH

Example for 1280

-s 1280

or

-s 1280 1280

NOTE: To simplify the ONNX model

--simplify

NOTE: To use dynamic batch-size (DeepStream >= 6.1)

--dynamic

NOTE: To use static batch-size (example for batch-size = 4)

--batch 4

5. Copy generated files

Copy the generated ONNX model file and labels.txt file (if generated) to the DeepStream-Yolo-Seg folder.

Compile the lib

1. Open the DeepStream-Yolo-Seg folder and compile the lib

2. Set the CUDA_VER according to your DeepStream version

export CUDA_VER=XY.Z

• x86 platform

  DeepStream 8.0 = 12.8
  DeepStream 7.1 = 12.6
  DeepStream 7.0 / 6.4 = 12.2
  DeepStream 6.3 = 12.1
  DeepStream 6.2 = 11.8
  DeepStream 6.1.1 = 11.7
  DeepStream 6.1 = 11.6
  DeepStream 6.0.1 / 6.0 = 11.4
  

• Jetson platform

  DeepStream 8.0 = 13.0
  DeepStream 7.1 = 12.6
  DeepStream 7.0 / 6.4 = 12.2
  DeepStream 6.3 / 6.2 / 6.1.1 / 6.1 = 11.4
  DeepStream 6.0.1 / 6.0 = 10.2
  

3. Make the lib

make -C nvdsinfer_custom_impl_Yolo_seg clean && make -C nvdsinfer_custom_impl_Yolo_seg

Edit the config_infer_primary_yoloV7_seg file

Edit the config_infer_primary_yoloV7_seg.txt file according to your model (example for YOLOv7-Seg)

[property]
...
onnx-file=yolov7-seg.onnx
...
num-detected-classes=80
...
parse-bbox-func-name=NvDsInferParseYoloSeg
...

NOTE: To output the masks, use

[property]
...
output-instance-mask=1
segmentation-threshold=0.5
...

NOTE: The YOLOv7-Seg resizes the input with center padding. To get better accuracy, use

[property]
...
maintain-aspect-ratio=1
symmetric-padding=1
...