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# coding = utf-8
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# 圈出图片中所有的人脸
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import numpy as np
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import math
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import cv2
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import dlib
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path = '/Users/yanshao/Desktop/img/timg.jpeg'
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Model = '/Users/yanshao/dlib/shape_predictor_5_face_landmarks.dat'
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# 首先把图片转化为方形
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detector = dlib.get_frontal_face_detector()
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predictor = dlib.shape_predictor(Model)
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def preprocess():
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image = cv2.imread(path)
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height, width, chl = image.shape[0], image.shape[1], image.shape[2]
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rec = int(max(height, width) * 1.5)
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pic = np.zeros((rec, rec, chl), np.uint8)
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baseh, basew = (rec - height) // 2, (rec - width) // 2
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pic[baseh:height + baseh, basew:width + basew] = image
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return pic, rec
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# 为了检测出图片中的所有人脸，我们每次把图片翻转45度
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def get_dist(point1, point2):
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return math.sqrt((point1[0]-point2[0])*(point1[0]-point2[0]) +
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(point1[1]-point2[1])*(point1[1]-point2[1]))
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def get_pos(point, M):
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return np.linalg.solve([[M[0][0], M[0][1]],
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[M[1][0], M[1][1]]],
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[point[0]-M[0][2], point[1]-M[1][2]]).astype(np.int32)
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pic, rec = preprocess()
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center = (rec//2,rec//2)
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list = []
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for ang in range(0, 8):
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M = cv2.getRotationMatrix2D(center, 45*ang, 1)
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pic2 = cv2.warpAffine(pic, M, (rec, rec))
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dets = detector(pic2, 1)
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print(len(dets))
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for face in dets:
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left, right, top, bot = face.left(), face.right(), face.top(), face.bottom()
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LT, RB = get_pos((left, top), M), get_pos((right, bot), M)
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list.append(((LT[0]+RB[0])//2, (LT[1]+RB[1])//2, (right-left)//2))
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cv2.destroyAllWindows()
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length = len(list)
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for i in range(0, length):
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flag = False
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for j in range(0, i):
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if get_dist(list[i], list[j]) < list[i][2]+list[j][2]:
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flag = True
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if not flag:
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cv2.circle(pic, (list[i][0], list[i][1]), list[i][2], (0, 255, 0))
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cv2.imshow("img", pic)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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