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import sys
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import numpy as np
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import os
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import cv2
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IMAGE_SIZE = 128
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def resize_image(image,height = IMAGE_SIZE,width = IMAGE_SIZE):
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top,bottom,left,right = 0,0,0,0
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#获取图像大小
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h,w,_ = image.shape
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#对于长宽不一的，取最大值
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longest_edge = max(h,w)
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#计算较短的边需要加多少像素
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if h < longest_edge:
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dh = longest_edge - h
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top = dh // 2
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bottom = dh - top
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elif w < longest_edge:
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dw = longest_edge - w
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left = dw // 2
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right = dw - left
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else:
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pass
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#定义填充颜色
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BLACK = [0,0,0]
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#给图像增加边界，使图片长、宽等长，cv2.BORDER_CONSTANT指定边界颜色由value指定
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constant_image = cv2.copyMakeBorder(image,top,bottom,left,right,cv2.BORDER_CONSTANT,value=BLACK)
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return cv2.resize(constant_image,(height,width))
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#读取数据
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images = [] #数据集
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labels = [] #标注集
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def read_path(path_name):
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for dir_item in os.listdir(path_name):
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full_path = path_name + '\\' + dir_item
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if os.path.isdir(full_path):
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read_path(full_path)
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else:
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#判断是人脸照片
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if dir_item.endswith('.jpg'):
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image = cv2.imread(full_path)
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image = resize_image(image)
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images.append(image)
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labels.append(path_name)
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return images,labels
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#为每一类数据赋予唯一的标签值
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def label_id(label,users,user_num):
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for i in range(user_num):
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if label.endswith(users[i]):
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return i
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#从指定位置读数据
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def load_dataset(path_name):
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users = os.listdir(path_name)
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user_num = len(users)
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images,labels = read_path(path_name)
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images_np = np.array(images)
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#每个图片夹都赋予一个固定唯一的标签
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labels_np = np.array([label_id(label,users,user_num) for label in labels])
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return images_np,labels_np
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