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  • 把图片按照指定大小剪裁,不够的地方加黑边

     1 # -*- coding: utf-8 -*-
     2 
     3 import os
     4 import sys
     5 import numpy as np
     6 import cv2
     7 
     8 IMAGE_SIZE = 224
     9 
    10 
    11 # 按照指定图像大小调整尺寸
    12 def resize_image(image, height=IMAGE_SIZE, width=IMAGE_SIZE):
    13     top, bottom, left, right = (0, 0, 0, 0)
    14 
    15     # 获取图像尺寸
    16     h, w, _ = image.shape
    17 
    18     # 对于长宽不相等的图片,找到最长的一边
    19     longest_edge = max(h, w)
    20 
    21     # 计算短边需要增加多上像素宽度使其与长边等长
    22     if h < longest_edge:
    23         dh = longest_edge - h
    24         top = dh // 2
    25         bottom = dh - top
    26     elif w < longest_edge:
    27         dw = longest_edge - w
    28         left = dw // 2
    29         right = dw - left
    30     else:
    31         pass
    32 
    33         # RGB颜色
    34     BLACK = [0, 0, 0]
    35 
    36     # 给图像增加边界,是图片长、宽等长,cv2.BORDER_CONSTANT指定边界颜色由value指定
    37     constant = cv2.copyMakeBorder(image, top, bottom, left, right, cv2.BORDER_CONSTANT, value=BLACK)
    38 
    39     # 调整图像大小并返回
    40     return cv2.resize(constant, (height, width))
    41 
    42 
    43 # 读取训练数据
    44 images = []
    45 labels = []
    46 
    47 
    48 def read_path(path_name):
    49     for dir_item in os.listdir(path_name):
    50         # 从初始路径开始叠加,合并成可识别的操作路径
    51         full_path = os.path.abspath(os.path.join(path_name, dir_item))
    52 
    53         if os.path.isdir(full_path):  # 如果是文件夹,继续递归调用
    54             read_path(full_path)
    55         else:  # 文件
    56             if dir_item.endswith('.jpg'):
    57                 image = cv2.imread(full_path)
    58                 image = resize_image(image, IMAGE_SIZE, IMAGE_SIZE)
    59 
    60                 # 放开这个代码,可以看到resize_image()函数的实际调用效果
    61                 # cv2.imwrite('1.jpg', image)
    62 
    63                 images.append(image)
    64                 labels.append(path_name)
    65 
    66     return images, labels
    67 
    68 
    69 # 从指定路径读取训练数据
    70 def load_dataset(path_name):
    71     images, labels = read_path(path_name)
    72 
    73     # 将输入的所有图片转成四维数组,尺寸为(图片数量*IMAGE_SIZE*IMAGE_SIZE*3)
    74     # 我和闺女两个人共1200张图片,IMAGE_SIZE为64,故对我来说尺寸为1200 * 64 * 64 * 3
    75     # 图片为64 * 64像素,一个像素3个颜色值(RGB)
    76     images = np.array(images)
    77     print(images.shape)
    78 
    79     # 标注数据,'me'文件夹下都是我的脸部图像,全部指定为0,另外一个文件夹下是闺女的,全部指定为1
    80     labels = np.array([0 if label.endswith('me') else 1 for label in labels])
    81 
    82     return images, labels
    83 
    84 path = 'D:/pycode/facial-keypoints-master/test/'
    85 if __name__ == '__main__':
    86     img =  cv2.imread(path+'000891.jpg')
    87     image = resize_image(img)
    88     cv2.imshow('img', image)
    89     cv2.imwrite("D:\1.jpg", image)
    90     cv2.waitKey(0)
    91     cv2.destroyAllWindows()
    92 
    93     if len(sys.argv) != 2:
    94         print("Usage:%s path_name
    " % path)
    95     else:
    96         images, labels = load_dataset(path)
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  • 原文地址:https://www.cnblogs.com/ansang/p/8491750.html
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