用自己的圖片構(gòu)建cifar10 binary格式的數(shù)據(jù)

標(biāo)簽（空格分隔）： 未分類

摘要

• 本文主要討論用python構(gòu)建cifar10 binary version數(shù)據(jù)
• 環(huán)境：windows顷帖， python3.6
• 本文最后更新日期是2018.04.13，因?yàn)榘姹静町愒斐傻膯?wèn)題請(qǐng)見(jiàn)諒

正文

tensorflow教程中的卷積神經(jīng)網(wǎng)絡(luò)一節(jié)厌衔，利用cifar10數(shù)據(jù)做分類，效果還不錯(cuò)茵瀑，那么我們能不能用這個(gè)模型去訓(xùn)練做其他的圖片分類呢酵使？
tensorflow教程的卷積神經(jīng)網(wǎng)絡(luò)教程中文網(wǎng)址
tensorflow教程的卷積神經(jīng)網(wǎng)絡(luò)教程英文網(wǎng)址
答案當(dāng)然是可以，但是教程給的模型是利用cifar10 binary格式的鸵荠，所以需要我們事先把我們的圖片數(shù)據(jù)轉(zhuǎn)成cifar10 binary格式簸呈。
教程給的模型代碼
cifar10 dataset網(wǎng)址
cifar10 binary version如下：

cifar10 binary version.png

# -*- coding: UTF-8 -*-

import cv2
import os
import numpy as np

DATA_LEN = 3072
CHANNEL_LEN = 1024
SHAPE = 32


def imread(im_path, shape=None, color="RGB", mode=cv2.IMREAD_UNCHANGED):
    im = cv2.imread(im_path, cv2.IMREAD_UNCHANGED)
    if color == "RGB":
        im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
    if shape != None:
        assert isinstance(shape, int)
        im = cv2.resize(im, (shape, shape))
    return im


def read_data(filename, data_path, shape=None, color='RGB'):
    """
       filename (str): a file
         data file is stored in such format:
           image_name  label
       data_path (str): image data folder
       return (numpy): a array of image and a array of label
    """
    if os.path.isdir(filename):
        print("Can't found data file!")
    else:
        f = open(filename)
        lines = f.read().splitlines()
        count = len(lines)
        data = np.zeros((count, DATA_LEN), dtype=np.uint8)
        # label = np.zeros(count, dtype=np.uint8)
        lst = [ln.split(' ')[0] for ln in lines]
        label = [int(ln.split(' ')[1]) for ln in lines]

        idx = 0
        s, c = SHAPE, CHANNEL_LEN
        for ln in lines:
            fname, lab = ln.split(' ')
            im = imread(os.path.join(data_path, fname), shape=s, color='RGB')
            '''
            im = cv2.imread(os.path.join(data_path, fname), cv2.IMREAD_UNCHANGED)
            im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
            im = cv2.resize(im, (s, s))
            '''
            data[idx, :c] = np.reshape(im[:, :, 0], c)
            data[idx, c:2 * c] = np.reshape(im[:, :, 1], c)
            data[idx, 2 * c:] = np.reshape(im[:, :, 2], c)
            label[idx] = int(lab)
            idx = idx + 1

        return data, label, lst


def py2bin(data, label):
    label_arr = np.array(label).reshape(len(label), 1)
    label_uint8 = label_arr.astype(np.uint8)
    arr = np.hstack((label_uint8, data))

    with open('./bin/train_batch', 'wb') as f:
        for element in arr.flat:
            f.write(element)


def imagelist():
    directory_normal = r"data/normal"   #原始圖片位置，32*32 pixel
    file_train_list = r"data/image_train_list.txt"  #構(gòu)建imagelist輸出位置
    with open(file_train_list, "a") as f:
        for filename in os.listdir(directory_normal):
            f.write(filename + " " + "0" + "\n")    #這里分類默認(rèn)全為0


if __name__ == '__main__':
    data_path = './data/normal'
    file_list = './data/image_train_list.txt'
    save_path = './bin'
    imagelist() #構(gòu)建imagelist
    data, label, lst = read_data(file_list, data_path, shape=32)    #將圖片像素?cái)?shù)據(jù)轉(zhuǎn)成矩陣和標(biāo)簽列表
    py2bin(data, label) #將像素矩陣和標(biāo)簽列表轉(zhuǎn)成cifar10 binary version

參考資料

[1]tensorflow教程的卷積神經(jīng)網(wǎng)絡(luò)教程

[2]cifar10 dataset

[3]制作自己的python版本的類CIFAR10數(shù)據(jù)集