Created
February 27, 2022 06:47
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Datasets to MNIST
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#!/usr/bin/env python3 | |
import os, argparse, secrets | |
import numpy as np | |
from array import * | |
from pathlib import Path | |
from PIL import Image | |
def data_2_mnist(data_folder:Path, img_size:int, output_folder:Path): | |
print("Dataset folder ->", data_folder) | |
print("Image size ->", img_size, "*", img_size) | |
print("Output folder ->", output_folder) | |
categories = os.listdir(data_folder) | |
ind_categories = [os.path.isdir(os.path.join(data_folder, i)) for i in categories] | |
categories = [categories[i] for i, x in enumerate(ind_categories) if x] | |
data_set = [] | |
data = array('B') | |
header = array('B') | |
label = array('B') | |
num_files = 0 | |
num_cat = 0 | |
width = img_size | |
height = img_size | |
for cat in categories: | |
cat_folder = os.path.join(data_folder, cat) | |
cat_files = os.listdir(cat_folder) | |
print('Using index', num_cat, 'as category', cat) | |
for file in cat_files: | |
num_files += 1 | |
file_path = os.path.join(cat_folder, file) | |
img = Image.open(file_path) | |
img = img.resize(size=(width, height), resample=Image.LANCZOS) | |
img = np.asarray(img) | |
data_set.append((num_cat, img)) | |
num_cat += 1 | |
secure_random = secrets.SystemRandom() | |
for pair in secure_random.sample(data_set, len(data_set)): | |
label.append(np.uint8(pair[0])) | |
for x in range(0, width): | |
for y in range(0, height): | |
data.append(np.uint8(pair[1][x, y])) | |
hexval = "{0:#0{1}x}".format(num_files, 6) | |
header.extend([0, 0, 8, 1, 0, 0]) | |
header.append(int('0x' + hexval[2:][:2], 16)) | |
header.append(int('0x' + hexval[2:][2:], 16)) | |
label = header + label | |
header.extend([0, 0, 0, width, 0, 0, 0, height]) | |
header[3] = 3 | |
data = header + data | |
output_file = open(os.path.join(output_folder, 'images.idx3-ubyte'), 'wb') | |
data.tofile(output_file) | |
output_file.close() | |
output_file = open(os.path.join(output_folder, 'labels.idx1-ubyte'), 'wb') | |
label.tofile(output_file) | |
output_file.close() | |
if __name__ == '__main__': | |
parser = argparse.ArgumentParser(description='Convert jpg/png datasets to ubyte MNIST.') | |
parser.add_argument('-i', '--data_dir', type=Path, required=True, help='the path of datasets folder which have sub-folders contained images with its labels') | |
parser.add_argument('-s', '--img_size', type=int, required=False, default=28, help='the pixels of rect image in MNIST') | |
parser.add_argument('-o', '--out_dir', type=Path, required=True, help='the path of converted MNIST to store') | |
args = parser.parse_args() | |
data_2_mnist(args.data_dir, args.img_size, args.out_dir) |
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