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import numpy as npimport cv2
sun = cv2.imread('E:/python/picture/sun.jpg')
sun = cv2.resize(sun, dsize=(617, 800))# 级联分类器detector = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml') # 识别人脸 导入人脸识别数据face_zone = detector.detectMultiScale(sun, scaleFactor=1.2, minNeighbors=5) # 人脸区域
# x，y是坐标 w，h宽高for x, y, w, h in face_zone: color = np.random.randint(0, 256, size=3)# 方形 cv2.rectangle(sun, pt1=(x, y), pt2=(x + w, y + w), color=color.tolist()) # 将识别出来的图片标记出来正方形# 圆形 cv2.circle(sun, center=(x+w//2, y+h//2), radius=w//2, color=color.tolist(), thickness=2) cv2.imshow('sun', sun) while True:
 if ord('q') == cv2.waitKey(30000): break cv2.destroyAllWindows()  

import numpy as npimport cv2import random

cap = cv2.VideoCapture('E:/python/video/2011.mp4') # 读取视频数据# cap = cv2.VideoCapture(0) # 参数为0 那么会调用摄像头.flag, frame = cap.read() # 读取视频中的其中一张照片cv2.waitKey(0)cv2.destroyAllWindows()# cap.get(propId=cv2.CAP_PROP_FPS) # 调试部分 获取视频的每秒多少帧 保证原视频的数据不变# cap.get(propId=cv2.CAP_PROP_FOURCC) # 编码格式# cap.get(propId=cv2.CAP_PROP_FRAME_COUNT) # 获取帧数量# cap.get(propId=cv2.CAP_PROP_FRAME_HEIGHT) # 获取图片高度# cap.get(propId=cv2.CAP_PROP_FRAME_WIDTH) # 获取图片宽度
h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))+1 # 获取图片高度 可大不可小w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))+1 # 获取图片宽度# 保存视频 四个参数 第一个是文件名 第二个视频编码 第三个是视频帧数 第四个是视频帧尺寸videoWrite = cv2.VideoWriter('E:/python/video/{}.mp4 '.format(random.random()), cv2.VideoWriter_fourcc('M', 'P', '4', 'v'), 24, (w, h))detector = cv2.CascadeClassifier(r'./haarcascade_frontalface_default.xml') # 导入人脸识别数据while cap.isOpened(): flag, frame = cap.read() if not flag: break
 gray = cv2.cvtColor(frame, code=cv2.COLOR_BGR2GRAY) face_zone = detector.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=4) # img_png = cv2.imread('E:/python/picture/11.jpg') # img_png = cv2.resize(img_png, (w, h)) for x, y, w, h in face_zone: # gray[y:y+w, x:x+h] = img_png color = np.random.randint(0, 256, size=3) # 圆形标记 cv2.circle(frame, center=(x+w//2, y+h//2), radius=w//2, color=[0, 0, 255], thickness=2) # 方形标记 cv2.rectangle(frame, pt1=(x, y), pt2=(x + w, y + w), color=color.tolist()) videoWrite.write(frame) if not flag: break cv2.imshow('role', frame) if ord('q') == cv2.waitKey(1): # 保证每一帧读取 视频正常显示 breakcv2.destroyAllWindows()cap.release()videoWrite.release()