是用opencv设计一个基于摄像头的图像识别系统

import cv2
import numpy as np

# 打开摄像头
cap = cv2.VideoCapture(0)

# 加载分类器
shape_classifier = cv2.CascadeClassifier('shape_classifier.xml')
color_classifier = cv2.CascadeClassifier('color_classifier.xml')

# 设置输出波形参数
waveforms = {
    'circle': {'freq': 0.1, 'vpp': 10},
    'square': {'freq': 1, 'vpp': 1},
    'other': {'freq': 10, 'vpp': 0.1}
}

while True:
    # 读取图像
    ret, frame = cap.read()

    # 预处理图像
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray, (5, 5), 0)
    edges = cv2.Canny(blur, 50, 200)

    # 检测形状和颜色
    shapes = shape_classifier.detectMultiScale(gray, 1.3, 5)
    colors = color_classifier.detectMultiScale(edges, 1.3, 5)

    for (x, y, w, h) in shapes:
        # 绘制矩形框
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)

        # 输出波形信息
        for (cx, cy, cw, ch) in colors:
            if x < cx < x + w and y < cy < y + h:
                color = frame[cy + ch // 2, cx + cw // 2]
                if np.all(color == [0, 0, 255]):
                    waveform = waveforms.get('circle')
                elif np.all(color == [0, 255, 255]):
                    waveform = waveforms.get('square')
                else:
                    waveform = waveforms.get('other')
                print('freq = {}, vpp = {}'.format(waveform['freq'], waveform['vpp']))

    # 显示图像
    cv2.imshow('frame', frame)

    # 退出循环
    if cv2.waitKey(1) &amp; 0xFF == ord('q'):
        break

# 关闭摄像头
cap.release()

# 关闭窗口
cv2.destroyAllWindows()