haarcascades人脸检测

图像人脸检测

# -*- coding: utf-8 -*-
import cv2
import numpy as np

# 静态图像中的人脸检测
def StaticDetect(filename):
    # 创建一个级联分类器 加载一个 .xml 分类器文件. 它既可以是Haar特征也可以是LBP特征的分类器.
    face_cascade = cv2.CascadeClassifier('data_cascades/haarcascades/haarcascade_frontalface_default.xml')
    # 加载图像
    img = cv2.imread(filename)
    # 转换为灰度图
    gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # 进行人脸检测，传入scaleFactor，minNegihbors，分别表示人脸检测过程中每次迭代时图像的压缩率以及
    # 每个人脸矩形保留近似数目的最小值
    # 返回人脸矩形数组
    faces = face_cascade.detectMultiScale(gray_img, 1.3, 5)
    for (x, y, w, h) in faces:
        # 在原图像上绘制矩形
        img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
    cv2.namedWindow('Face Detected！')
    cv2.imshow('Face Detected！', img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

视频人脸检测

# -*- coding: utf-8 -*-
import numpy as np
import cv2
#多张图片
cap=cv2.VideoCapture("C:/Users/ie/Desktop/lemon/law.mp4")
#保存视频----参数：文件名（.avi）；视频编码；参数帧率fps；尺寸
fourcc=cv2.VideoWriter_fourcc('M','P','4','2')
w=int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
h=int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
video_writer=cv2.VideoWriter("C:/Users/ie/Desktop/lemon/law.avi",fourcc,fps=10,frameSize=(w,h))
face_detector=cv2.CascadeClassifier("C:/Users/ie/Desktop/lemon/haarcascade_frontalface_default.xml")
#读取状态；帧
success,frame=cap.read()
while(success):  
    gray=cv2.cvtColor(frame,code=6)
    face_zone= face_detector.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=5,minSize=(50,50))
    for x,y,w,h in face_zone:
        cv2.circle(frame,center=(x+w//2,y+h//2),radius=w//2,color=[0,0,255],thickness=2)
    cv2.imshow('law',frame) 
    video_writer.write(frame)
    if cv2.waitKey(1000//24)==ord('q'):
        break
    success,frame=cap.read()    
cap.release()
video_writer.release()
cv2.destroyAllWindows()

摄像头人脸检测

# -*- coding: utf-8 -*-
import numpy as np
import cv2

eye_detector = cv2.CascadeClassifier("C:/Users/ie/Desktop/lemon/haarcascade_eye.xml")
mouth_detector = cv2.CascadeClassifier("C:/Users/ie/Desktop/lemon/haarcascade_mcs_mouth.xml")
face_detector = cv2.CascadeClassifier("C:/Users/ie/Desktop/lemon/haarcascade_frontalface_default.xml")
# 参数0代表获取电脑中的摄像头
cap = cv2.VideoCapture(0)
# 保存视频----参数：文件名（.avi）；视频编码；参数帧率fps；尺寸
fourcc = cv2.VideoWriter_fourcc('M', 'P', '4', '2')
w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
video_writer = cv2.VideoWriter("C:/Users/ie/Desktop/lemon/luzi.avi", fourcc, fps=10, frameSize=(w, h))
while (cap.isOpened()):
    success, frame = cap.read()
    gray = cv2.cvtColor(frame, code=cv2.COLOR_BGR2GRAY)
    face_zone = face_detector.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5, minSize=(50, 50))
    for x, y, w, h in face_zone:
        cv2.rectangle(frame, pt1=(x, y), pt2=(x + w, y + h), color=[0, 0, 255], thickness=2)
    # 眼睛
    x, y, w, h in face_zone
    head = gray[y:y + h, x:x + w]
    split_h = int(h * 0.6)
    up_head = head[0:split_h]
    down_head = head[split_h:]
    eye_zone = eye_detector.detectMultiScale(up_head, scaleFactor=1.2, minNeighbors=5, minSize=(50, 50))
    for ex, ey, ew, eh in eye_zone:
        cv2.circle(frame, center=(x + ex + ew // 2, y + ey + eh // 2), radius=ew // 2, color=[0, 0, 255], thickness=2)
    mouth_zone = mouth_detector.detectMultiScale(down_head, scaleFactor=1.2, minNeighbors=5, minSize=(50, 50))
    for mx, my, mw, mh in eye_zone:
        # cv2.circle(frame,center=(x+mx+mw//2,y+my+mh//2),radius=mw//2,color=[0,0,255],thickness=2)
        cv2.rectangle(frame, pt1=(x + mx, y + my + split_h), pt2=(x + mx + mw, +y + my + mh + split_h),
                      color=[0, 0, 255], thickness=2)
    cv2.imshow('cap', frame)
    if cv2.waitKey(1000 // 24) == ord('q'):
        break
cap.release()
video_writer.release()
cv2.destroyAllWindows()