Python基于opencv的人脸识别+马赛克处理

import cv2

camera = cv2.VideoCapture(0)

frame_width = int(camera.get(3))
frame_height = int(camera.get(4))

#  训练好的模型
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

#  处理视频文件
fourcc = cv2.VideoWriter_fourcc(*'mp4v')   # 编解码器
out = cv2.VideoWriter('test.mp4', fourcc, 30.0, (frame_width, frame_height))  # 保存位置 编解码器 帧数 分辨率

while camera.isOpened():
    ret, frame = camera.read()
    frame = cv2.flip(frame, 1)  # 参数：0垂直镜像 1水平镜像
    #  图像处理
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)  #  灰度图像
    faces = face_cascade.detectMultiScale(gray, 1.1, 5)
    if ret:
        for (x, y, w, h) in faces:
            cv2.rectangle(frame, (x,  y), (x + w, y + h), (0, 255, 0), 2)  #  人脸旁边的框
            cv2.putText(frame, "Unknown", (x + 5, y - 5), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 1)  #  框旁边的标签
            #  对人脸进行马赛克处理
            face_img = frame[y:y + h, x:x + w]
            face_img = cv2.resize(face_img, (w//30, h//30))  #  缩小人脸区域
            face_img = cv2.resize(face_img, (w, h), interpolation=cv2.INTER_NEAREST)  #  恢复人脸区域
            #  处理后的图像放回源中
            frame[y:y+h, x:x+w] = face_img
        out.write(frame)
        cv2.imshow("Test", frame)
        #  按Q停止程序
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    else:
        break

#  释放对象
out.release()
camera.release()
cv2.destroyAllWindows()