Getting started with opencv-simple face detection for pictures, videos, and cameras

Picture face detection:

import cv2 as cv
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['SimHei']      # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False        # 用来正常显示负号
# 加载图片，灰度图方式读取
img = cv.imread('img/img31.jpg')
gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)

# 实例化级联分类器 # 加载分类器
face_cas =cv.CascadeClassifier( "haarcascade_frontalface_default.xml" )
face_cas.load('haarcascade_frontalface_default.xml')
eyes_cas = cv.CascadeClassifier("haarcascade_eye.xml")
eyes_cas.load("haarcascade_eye.xml")

# 调用识别人脸，根据灰度图来查找目标
faceRects = face_cas.detectMultiScale( gray, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))

for faceRect in faceRects:
    # 人脸检测
    x, y, w, h = faceRect
    # 框出人脸
    cv.rectangle(img, (x, y), (x + h, y + w), (0,255,0), 3)
    # 识别出的人脸中进行眼睛检测
    roi_color = img[y:y+h, x:x+w]   # 人脸区域内找眼睛
    roi_gray = gray[y:y+h, x:x+w]   # 人脸区域内找眼睛
    # 根据灰度图来查找目标
    eyes = eyes_cas.detectMultiScale(roi_gray)
    for (ex, ey, ew, eh) in eyes:
        cv.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
# 5. 检测结果的绘制
plt.figure(figsize=(8,6),dpi=100)
plt.imshow(img[:,:,::-1]),plt.title('检测结果')
plt.xticks([]), plt.yticks([])
plt.show()

Video face detection:

import cv2 as cv
import matplotlib.pyplot as plt

# 读取视频
cap = cv.VideoCapture("img/video2.mp4")
while(cap.isOpened()):
    ret, frame = cap.read()
    if ret == True:
        gray = cv.cvtColor(frame,cv.COLOR_BGR2GRAY)
        face_cas = cv.CascadeClassifier( "haarcascade_frontalface_default.xml" )
        face_cas.load('haarcascade_frontalface_default.xml')
        # 4.调用识别人脸
        faceRects = face_cas.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))
        for faceRect in faceRects:
            x, y, w, h = faceRect
            # 框出人脸
            cv.rectangle(frame, (x, y), (x + h, y + w),(0,255,0), 3)
        cv.imshow("frame",frame)
        if cv.waitKey(1) & 0xFF == ord('q'):
            break
# 5. 释放资源
cap.release()
cv.destroyAllWindows()

Camera face detection:

import cv2 as cv
import matplotlib.pyplot as plt

# 读取视频
cap = cv.VideoCapture(0)
while(cap.isOpened()):
    ret, frame = cap.read()
    if ret == True:
        gray = cv.cvtColor(frame,cv.COLOR_BGR2GRAY)
        face_cas = cv.CascadeClassifier( "haarcascade_frontalface_default.xml" )
        face_cas.load('haarcascade_frontalface_default.xml')
        # 4.调用识别人脸
        faceRects = face_cas.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))
        for faceRect in faceRects:
            x, y, w, h = faceRect
            # 框出人脸
            cv.rectangle(frame, (x, y), (x + h, y + w),(0,255,0), 3)
        cv.imshow("frame",frame)
        if cv.waitKey(1) & 0xFF == ord('q'):
            break
# 5. 释放资源
cap.release()
cv.destroyAllWindows()

cv Xiaobai, hope the boss will give pointers