Example Code for Python - Object Classification Based on Computer YOLOv5

Hardware Preparation

• ESP32-S3 AI Camera Module x 1

Software Preparation

1. Python IDLE(https://www.python.org/)

Other Preparation Work

1. Burn the code to the module (use the code from Section 5.3 or 5.4).

2. Install Python (https://www.python.org/) if not already installed.

3. Install required libraries:

   • Press Win+R, type cmd to open the command prompt.

   • Run pip install opencv-python to install OpenCV.

   • Run pip install yolov5 to install the YOLOv5 library.

4. Open Python IDLE, go to File > Open..., select the appropriate Python file (yolo_5_3.py for Section 5.3 example or yolo_5_4.py for Section 5.4 example), and press F5 to run the script and view the results.

Sample Code

• Demo source code and firmware

Result

Additional Information

Notes:

• When using yolo_5_3.py, modify the IP address parameter.

• When using yolo_5_4.py, modify the cap = cv2.VideoCapture(0) parameter to specify the correct camera index.

What is the principle of object contour recognition?

Object contour recognition involves detecting the boundaries of objects in an image by analyzing changes in pixel intensity. Common steps include:

1. Preprocessing: Convert the image to grayscale and apply noise reduction.

2. Edge Detection: Use algorithms like Canny to identify edges.

3. Contour Extraction: Connect edge points to form continuous contours.

4. Postprocessing: Filter and analyze contours based on properties like area, perimeter, or shape.