yolov5.md

title
Using YOLOv5 Model for Object Detection with MaixPy

Concept of Object Detection

Object detection refers to identifying the position and category of targets in an image or video, such as detecting objects like apples and airplanes in a picture, and marking the position of these objects.

Unlike classification, object detection includes positional information, so the result is usually a rectangular box that frames the location of the object.

Using Object Detection in MaixPy

MaixPy comes with the YOLOv5 model by default, which can be used directly:

from maix import camera, display, image, nn, app

detector = nn.YOLOv5(model="/root/models/yolov5s.mud")

cam = camera.Camera(detector.input_width(), detector.input_height(), detector.input_format())
dis = display.Display()

while not app.need_exit():
    img = cam.read()
    objs = detector.detect(img, conf_th = 0.5, iou_th = 0.45)
    for obj in objs:
        img.draw_rect(obj.x, obj.y, obj.w, obj.h, color = image.COLOR_RED)
        msg = f'{detector.labels[obj.class_id]}: {obj.score:.2f}'
        img.draw_string(obj.x, obj.y, msg, color = image.COLOR_RED)
    dis.show(img)

Demonstration video: