split_dataset_list.py 5.0 KB
Newer Older
L
LutaoChu 已提交
1
# coding: utf8
W
wuyefeilin 已提交
2
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
L
LutaoChu 已提交
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import glob
import os.path
import argparse
import warnings
import numpy as np


def parse_args():
    parser = argparse.ArgumentParser(
        description=
        'A tool for proportionally randomizing dataset to produce file lists.')
    parser.add_argument('dataset_root', help='the dataset root path', type=str)
    parser.add_argument('images', help='the directory name of images', type=str)
    parser.add_argument('labels', help='the directory name of labels', type=str)
    parser.add_argument(
        '--split', help='', nargs=3, type=float, default=[0.7, 0.3, 0])
    parser.add_argument(
        '--label_class',
        help='label class names',
        type=str,
        nargs='*',
        default=['__background__', '__foreground__'])
    parser.add_argument(
        '--separator',
        dest='separator',
        help='file list separator',
        default=" ",
        type=str)
    parser.add_argument(
        '--format',
        help='data format of images and labels, e.g. jpg, npy or png.',
        type=str,
        nargs=2,
        default=['npy', 'png'])
    parser.add_argument(
        '--postfix',
        help='postfix of images or labels',
        type=str,
        nargs=2,
        default=['', ''])

    return parser.parse_args()


def get_files(path, format, postfix):
    pattern = '*%s.%s' % (postfix, format)

    search_files = os.path.join(path, pattern)
    search_files2 = os.path.join(path, "*", pattern)  # 包含子目录
    search_files3 = os.path.join(path, "*", "*", pattern)  # 包含三级目录

    filenames = glob.glob(search_files)
    filenames2 = glob.glob(search_files2)
    filenames3 = glob.glob(search_files3)

    filenames = filenames + filenames2 + filenames3

    return sorted(filenames)


def generate_list(args):
    separator = args.separator
    dataset_root = args.dataset_root
    if sum(args.split) != 1.0:
        raise ValueError("划分比例之和必须为1")

    file_list = os.path.join(dataset_root, 'labels.txt')
    with open(file_list, "w") as f:
        for label_class in args.label_class:
            f.write(label_class + '\n')

    image_dir = os.path.join(dataset_root, args.images)
    label_dir = os.path.join(dataset_root, args.labels)
    image_files = get_files(image_dir, args.format[0], args.postfix[0])
    label_files = get_files(label_dir, args.format[1], args.postfix[1])
    if not image_files:
        warnings.warn("No files in {}".format(image_dir))
    num_images = len(image_files)

    if not label_files:
        warnings.warn("No files in {}".format(label_dir))
    num_label = len(label_files)

    if num_images != num_label and num_label > 0:
        raise Exception("Number of images = {}    number of labels = {} \n"
                        "Either number of images is equal to number of labels, "
                        "or number of labels is equal to 0.\n"
                        "Please check your dataset!".format(
                            num_images, num_label))

    image_files = np.array(image_files)
    label_files = np.array(label_files)
    state = np.random.get_state()
    np.random.shuffle(image_files)
    np.random.set_state(state)
    np.random.shuffle(label_files)

    start = 0
    num_split = len(args.split)
    dataset_name = ['train', 'val', 'test']
    for i in range(num_split):
        dataset_split = dataset_name[i]
        print("Creating {}.txt...".format(dataset_split))
        if args.split[i] > 1.0 or args.split[i] < 0:
            raise ValueError(
                "{} dataset percentage should be 0~1.".format(dataset_split))

        file_list = os.path.join(dataset_root, dataset_split + '.txt')
        with open(file_list, "w") as f:
            num = round(args.split[i] * num_images)
            end = start + num
            if i == num_split - 1:
                end = num_images
            for item in range(start, end):
                left = image_files[item].replace(dataset_root, '')
                if left[0] == os.path.sep:
                    left = left.lstrip(os.path.sep)

                try:
                    right = label_files[item].replace(dataset_root, '')
                    if right[0] == os.path.sep:
                        right = right.lstrip(os.path.sep)
                    line = left + separator + right + '\n'
                except:
                    line = left + '\n'

                f.write(line)
                print(line)
            start = end


if __name__ == '__main__':
    args = parse_args()
    generate_list(args)