OpenCV进行人脸提取，RGB以及HSV分别提取+实验报告.zip

import cv2 import numpy as np def rgb(img): # 图像处理 rgb = cv2.cvtColor(img, cv2.COLOR_BGR2YCR_CB) cv2.imshow("rgb",rgb) (y, cr, cb) = cv2.split(rgb) print(cr.shape) colorInset = np.zeros((cr.shape), dtype=np.uint8) # 表示这是颜色区间 cv2.imshow("inset",colorInset) # 参数（图像，中心位置，轴线，角度，开始角度，结束角度，颜色，厚度） cv2.ellipse(colorInset, (113, 155), (23, 15), 43, 0, 360, (255, 255, 255), -1) # 画了一片黑 skin = np.zeros(cr.shape, dtype=np.uint8) (x, y) = cr.shape for i in range(0, x): for j in range(0, y): CR = rgb[i, j, 1] CB = rgb[i, j, 2] if colorInset[CR, CB] > 0: skin[i, j] = 255 cv2.imshow('mask', skin) dst = cv2.bitwise_and(img, img, mask=skin) v1 = np.hstack((img, dst)) cv2.imshow("all", v1) def hsv(imgout): hsv = cv2.cvtColor(imgOut, cv2.COLOR_BGR2HSV) cv2.imshow("hsv",hsv) lower = np.array([0,2,130]) upper = np.array([179,200,254]) # 蒙版 mask = cv2.inRange(hsv, lower, upper) dst = cv2.bitwise_and(imgOut, imgOut, mask=mask) cv2.imshow("hsvmask", mask) v1 = np.hstack((imgOut, dst)) cv2.imshow("hsvall", v1) cv2.waitKey() def getface(img): faceCascade = cv2.CascadeClassifier("haarcascade_frontalface_alt2.xml") imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) faces = faceCascade.detectMultiScale(imgGray,1.1,4) width = 300 imgOut = img for (x, y, w, h) in faces: cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2) # ******************************提取人脸部分，并且进行颜色识别，肤色 pts1 = np.float32([[x, y], [x + w, y], [x, y + h], [x + w, y + h]]) height = int(h / w * width) pts2 = np.float32([[0, 0], [width, 0], [0, height], [width, height]]) matrix = cv2.getPerspectiveTransform(pts1, pts2) imgOut = cv2.warpPerspective(img, matrix, (width, height)) # ******************************提取人脸部分，并且进行颜色识别，肤色 return imgOut if __name__ == '__main__': for i in range(1,11): src = 'people/'+str(i)+'.png' img = cv2.imread(src) imgOut = getface(img) rgb(imgOut) hsv(imgOut) while True: if cv2.waitKey(1) & 0xFF == ord('q'): break