General Object Recognition based on YOLO-V5 Model

Execute the following steps to recognize general objects based on YOLO-V5 Model:

Step:

To run Python application:

Enter the third-party application directory, demo, of YOLO-V5 and execute the command to run the Python application:

cd /usr/share/opencv4/yolo-v5/
python3 yolov5.py --device 4
Tip: Parameter Information:

Added --device and number 1 or 4 as an input parameter to specify the number of the video device capturing a video stream.

Result:

  • HDMI monitor displays the real-time video stream from a webcam;
  • HDMI monitor displays real-time drawings of bounding boxes, labeling the objects recognized by the model, and displaying their names and confidence level;
  • The inference time per frame is displayed on the upper left corner, which translates to an approximate inference frame rate of 0.6 to 1.1 fps;
Figure 1. General Object Recognition based on YOLO-V5 ONNX Model