一、人臉檢測

案例代碼如下:

import cv2
import numpy as np

video =  cv2.VideoCapture('1.mp4')
face_detector = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
while True:
    retval,image = video.read() #     retval boolean類型表名是否獲得了圖片
    if not retval:
        print('視頻讀取完成，沒有圖片')
        break
    faces = face_detector.detectMultiScale(image)
    for x,y,w,h in faces:
        cv2.rectangle(image,pt1=(x,y),pt2 = (x+w,y+h),color=[0,0,255],thickness=2)
    cv2.imshow('video',image)
    key = cv2.waitKey(1)
    if key == ord('q'):
        break

cv2.waitKey(1)
video.release()

二、馬賽克處理

視頻幀率、寬度、高度、圖片個數(shù)計算:

import cv2
import numpy as np

video =  cv2.VideoCapture('1.mp4')
# 獲得視頻中的屬性
fps = video.get(propId=cv2.CAP_PROP_FPS) #得到幀率
width = video.get(propId=cv2.CAP_PROP_FRAME_WIDTH) #寬度
height = video.get(propId=cv2.CAP_PROP_XI_HEIGHT) #高度
count = video.get(propId=cv2.CAP_PROP_FRAME_COUNT) #多少圖片
print('--視頻幀率',fps)
print(width,height,count)
face_detector = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
while True:
    retval,image = video.read() #     retval boolean類型表名是否獲得了圖片
    if not retval:
        print('視頻讀取完成，沒有圖片')
        break
    faces = face_detector.detectMultiScale(image)
    for x,y,w,h in faces:
        # cv2.rectangle(image,pt1=(x,y),pt2 = (x+w,y+h),color=[0,0,255],thickness=2)
        face = image[y:y+h,x:x+w]
        face = face[::10,::10]
        face = np.repeat(face,10,axis=0)
        face = np.repeat(face,10,axis =1)
        image[y:y+h,x:x+w] = face[:h,:w]

    cv2.imshow('video',image)
    key = cv2.waitKey(1)
    if key == ord('q'):
        break

cv2.waitKey(1)
video.release()

三、寫視頻

案例代碼如下:

import cv2
import numpy as np

video =  cv2.VideoCapture('1.mp4')
wr = cv2.VideoWriter(filename = 'gray.mp4',
                fourcc = cv2.VideoWriter.fourcc(*'MP4'),
                fps = 24, #視頻幀率
                framesize = (640,360)) #圖片尺寸
# 獲得視頻中的屬性
fps = video.get(propId=cv2.CAP_PROP_FPS) #得到幀率
width = video.get(propId=cv2.CAP_PROP_FRAME_WIDTH) #寬度
height = video.get(propId=cv2.CAP_PROP_XI_HEIGHT) #高度
count = video.get(propId=cv2.CAP_PROP_FRAME_COUNT) #多少圖片
print('--視頻幀率',fps)
print(width,height,count)
face_detector = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
while True:
    retval,image = video.read() #     retval boolean類型表名是否獲得了圖片
    if not retval:
        print('視頻讀取完成，沒有圖片')
        break
    image = cv2.resize(image,(640,360))
    gray = cv2.cvtColor(image,code = cv2.COLOR_BGR2GRAY)
    np.repeat(gray.reshape(360,640,1),3,axis=2) #藍綠紅變?yōu)槿S，但值是一樣的
    # wr.write(gray)
    faces = face_detector.detectMultiScale(image)
    for x,y,w,h in faces:
        # cv2.rectangle(image,pt1=(x,y),pt2 = (x+w,y+h),color=[0,0,255],thickness=2)
        face = image[y:y+h,x:x+w]
        face = face[::10,::10]
        face = np.repeat(face,10,axis=0)
        face = np.repeat(face,10,axis =1)
        image[y:y+h,x:x+w] = face[:h,:w]
    wr.write(image) #彩色圖片是三維的,而黑白圖片是二維的
    cv2.imshow('video',image)
    key = cv2.waitKey(1)
    if key == ord('q'):
        break

cv2.waitKey(1)
video.release()
wr.release()

四、攝像頭識別人臉

案例代碼如下:文章來源地址http://www.zghlxwxcb.cn/news/detail-602309.html

import cv2
import numpy as np

# 打開本機攝像頭
cap = cv2.VideoCapture(0)
face_detector = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')

while True:
    flag,frame = cap.read() #flag是否讀取了圖片
    if not flag:
        break
    # 轉(zhuǎn)為灰度圖片
    gray = cv2.cvtColor(frame,code = cv2.COLOR_BGR2GRAY)
    faces = face_detector.detectMultiScale(gray,scaleFactor=1.1,minNeighbors=10)
    for x,y,w,h in faces:
        cv2.rectangle(frame,
                      pt1=(x,y),
                      pt2=(x+w,y+h),
                      color=[0,0,255],
                      thickness=2)
    cv2.imshow('face',frame)
    key = cv2.waitKey(1000//24)
    if key == ord('q'):
        break

cv2.destroyAllWindows()
cap.release()

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