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# coding:utf-8
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import cv2
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import matplotlib.pyplot as plt
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import os
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_currentFilePath = os.path.split(os.path.realpath(__file__))[0]
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#opencv人脸检测分类器，可以进行更换，请根据左侧分类器选择你想用的填写其中
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############### Begin #############
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classifierFileName = "haarcascade_frontalface_alt.xml"
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face_cascade = cv2.CascadeClassifier(os.path.join(_currentFilePath, classifierFileName))
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############### End #############
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# 读取图片
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def read_directory(directory_name):
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_cnt = 0
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for filename in os.listdir(directory_name):
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if filename.lower().endswith(".png") is False and filename.lower().endswith(".jpg") is False:
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continue
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_pathToFile = directory_name + "/" + filename
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image = cv2.imread(_pathToFile)
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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# 探测图片中的人脸
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faces = face_cascade.detectMultiScale(
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gray,
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scaleFactor=1.15,
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minNeighbors=5,
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minSize=(5, 5),
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flags=cv2.CASCADE_SCALE_IMAGE)
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for (x, y, w, h) in faces:
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cv2.rectangle(image,(x,y),(x+w,y+h),(0,255,0),2)#直接在源操作了
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if len(faces) == 0:
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print('未检测出人脸')
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else:
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_pathToSavedFile = os.path.join(_currentFilePath, "./images/result/") + filename + ".rst.jpg"
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cv2.imwrite(_pathToSavedFile, image)
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print("生成结果成功!", _pathToSavedFile)
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print('检测到%d张人脸' % len(faces))
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print('检测成功!')
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_cnt = _cnt + 1
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if _cnt == 0:
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print("检测失败!")
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read_directory(os.path.join(_currentFilePath, "images/source"))
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