Created
December 31, 2017 08:28
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| import cv2 | |
| import os | |
| import sys | |
| import random | |
| out_dir = './my_faces' | |
| if not os.path.exists(out_dir): | |
| os.makedirs(out_dir) | |
| # 改变亮度与对比度 | |
| def relight(img, alpha=1, bias=0): | |
| w = img.shape[1] | |
| h = img.shape[0] | |
| #image = [] | |
| for i in range(0,w): | |
| for j in range(0,h): | |
| for c in range(3): | |
| tmp = int(img[j,i,c]*alpha + bias) | |
| if tmp > 255: | |
| tmp = 255 | |
| elif tmp < 0: | |
| tmp = 0 | |
| img[j,i,c] = tmp | |
| return img | |
| # 获取分类器 | |
| haar = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') | |
| # 打开摄像头 参数为输入流，可以为摄像头或视频文件 | |
| camera = cv2.VideoCapture(0) | |
| n = 1 | |
| while 1: | |
| if (n <= 10000): | |
| print('It`s processing %s image.' % n) | |
| # 读帧 | |
| success, img = camera.read() | |
| gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) | |
| faces = haar.detectMultiScale(gray_img, 1.3, 5) | |
| for f_x, f_y, f_w, f_h in faces: | |
| face = img[f_y:f_y+f_h, f_x:f_x+f_w] | |
| face = cv2.resize(face, (64,64)) | |
| ''' | |
| if n % 3 == 1: | |
| face = relight(face, 1, 50) | |
| elif n % 3 == 2: | |
| face = relight(face, 0.5, 0) | |
| ''' | |
| face = relight(face, random.uniform(0.5, 1.5), random.randint(-50, 50)) | |
| cv2.imshow('img', face) | |
| cv2.imwrite(out_dir+'/'+str(n)+'.jpg', face) | |
| n+=1 | |
| key = cv2.waitKey(30) & 0xff | |
| if key == 27: | |
| break | |
| else: | |
| break |
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