基于Python3+opencv 人脸检测代码

基于Python3+opencv 人脸检测代码

1.基于图片

 基于Python3+opencv 人脸检测代码_第1张图片

import cv2 as cv
import numpy as np


def face_detect_demo(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    face_detector = cv.CascadeClassifier("E:/opencv/build/etc/haarcascades/haarcascade_frontalface_alt.xml")
    faces = face_detector.detectMultiScale(gray, 1.1, 2)
    for x, y, w, h in faces:
        cv.rectangle(image, (x, y), (x+w, y+h), (0, 0, 255), 2)
    cv.imshow("result", image)

print("--------- Python OpenCV Tutorial ---------")
src = cv.imread("E:/opencv/sources/samples/data/lena.jpg")
face_detect_demo(src)

cv.waitKey(0)

cv.destroyAllWindows()

2. 基于摄像头

 基于Python3+opencv 人脸检测代码_第2张图片

 

import cv2 as cv
import numpy as np


def face_detect_demo(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    face_detector = cv.CascadeClassifier("E:/opencv/build/etc/haarcascades/haarcascade_frontalface_alt.xml")
    faces = face_detector.detectMultiScale(gray, 1.1, 2)
    for x, y, w, h in faces:
        cv.rectangle(image, (x, y), (x+w, y+h), (0, 0, 255), 2)
    cv.imshow("result", image)

print("--------- Python OpenCV Tutorial ---------")
capture = cv.VideoCapture(0)
cv.namedWindow("result", cv.WINDOW_AUTOSIZE)
while(True):
    ret, frame = capture.read()
    frame = cv.flip(frame, 1)
    face_detect_demo(frame)
    c = cv.waitKey(10)
    if c == 27: # ESC
        break
cv.waitKey(0)

cv.destroyAllWindows()

 

 

注:分类器在   opencv/build/etc/haarcascades/haarcascade_frontalface_alt.xml

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