folder.py 9.5 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# 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 os
import sys

from paddle.io import Dataset
L
LielinJiang 已提交
19
from paddle.utils import try_import
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

__all__ = ["DatasetFolder", "ImageFolder"]


def has_valid_extension(filename, extensions):
    """Checks if a file is a vilid extension.

    Args:
        filename (str): path to a file
        extensions (tuple of str): extensions to consider (lowercase)

    Returns:
        bool: True if the filename ends with one of given extensions
    """
    return filename.lower().endswith(extensions)


def make_dataset(dir, class_to_idx, extensions, is_valid_file=None):
    images = []
    dir = os.path.expanduser(dir)

    if extensions is not None:

        def is_valid_file(x):
            return has_valid_extension(x, extensions)

    for target in sorted(class_to_idx.keys()):
        d = os.path.join(dir, target)
        if not os.path.isdir(d):
            continue
        for root, _, fnames in sorted(os.walk(d, followlinks=True)):
            for fname in sorted(fnames):
                path = os.path.join(root, fname)
                if is_valid_file(path):
                    item = (path, class_to_idx[target])
                    images.append(item)

    return images


class DatasetFolder(Dataset):
    """A generic data loader where the samples are arranged in this way:

        root/class_a/1.ext
        root/class_a/2.ext
        root/class_a/3.ext

        root/class_b/123.ext
        root/class_b/456.ext
        root/class_b/789.ext

    Args:
        root (string): Root directory path.
        loader (callable|optional): A function to load a sample given its path.
        extensions (tuple[str]|optional): A list of allowed extensions.
            both extensions and is_valid_file should not be passed.
        transform (callable|optional): A function/transform that takes in
            a sample and returns a transformed version.
        is_valid_file (callable|optional): A function that takes path of a file
            and check if the file is a valid file (used to check of corrupt files)
            both extensions and is_valid_file should not be passed.

     Attributes:
        classes (list): List of the class names.
        class_to_idx (dict): Dict with items (class_name, class_index).
        samples (list): List of (sample path, class_index) tuples
        targets (list): The class_index value for each image in the dataset

    Example:

        .. code-block:: python

            import os
            import cv2
            import tempfile
            import shutil
            import numpy as np
97
            from paddle.vision.datasets import DatasetFolder
98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193

            def make_fake_dir():
                data_dir = tempfile.mkdtemp()

                for i in range(2):
                    sub_dir = os.path.join(data_dir, 'class_' + str(i))
                    if not os.path.exists(sub_dir):
                        os.makedirs(sub_dir)
                    for j in range(2):
                        fake_img = (np.random.random((32, 32, 3)) * 255).astype('uint8')
                        cv2.imwrite(os.path.join(sub_dir, str(j) + '.jpg'), fake_img)
                return data_dir

            temp_dir = make_fake_dir()
            data_folder = DatasetFolder(temp_dir)

            for items in data_folder:
                break
                
            shutil.rmtree(temp_dir)
    """

    def __init__(self,
                 root,
                 loader=None,
                 extensions=None,
                 transform=None,
                 is_valid_file=None):
        self.root = root
        self.transform = transform
        if extensions is None:
            extensions = IMG_EXTENSIONS
        classes, class_to_idx = self._find_classes(self.root)
        samples = make_dataset(self.root, class_to_idx, extensions,
                               is_valid_file)
        if len(samples) == 0:
            raise (RuntimeError(
                "Found 0 files in subfolders of: " + self.root + "\n"
                "Supported extensions are: " + ",".join(extensions)))

        self.loader = cv2_loader if loader is None else loader
        self.extensions = extensions

        self.classes = classes
        self.class_to_idx = class_to_idx
        self.samples = samples
        self.targets = [s[1] for s in samples]

    def _find_classes(self, dir):
        """
        Finds the class folders in a dataset.

        Args:
            dir (string): Root directory path.

        Returns:
            tuple: (classes, class_to_idx) where classes are relative to (dir), 
                    and class_to_idx is a dictionary.

        """
        if sys.version_info >= (3, 5):
            # Faster and available in Python 3.5 and above
            classes = [d.name for d in os.scandir(dir) if d.is_dir()]
        else:
            classes = [
                d for d in os.listdir(dir)
                if os.path.isdir(os.path.join(dir, d))
            ]
        classes.sort()
        class_to_idx = {classes[i]: i for i in range(len(classes))}
        return classes, class_to_idx

    def __getitem__(self, index):
        """
        Args:
            index (int): Index

        Returns:
            tuple: (sample, target) where target is class_index of the target class.
        """
        path, target = self.samples[index]
        sample = self.loader(path)
        if self.transform is not None:
            sample = self.transform(sample)

        return sample, target

    def __len__(self):
        return len(self.samples)


IMG_EXTENSIONS = ('.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm', '.tif',
                  '.tiff', '.webp')


def cv2_loader(path):
L
LielinJiang 已提交
194
    cv2 = try_import('cv2')
195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227
    return cv2.imread(path)


class ImageFolder(Dataset):
    """A generic data loader where the samples are arranged in this way:

        root/1.ext
        root/2.ext
        root/sub_dir/3.ext

    Args:
        root (string): Root directory path.
        loader (callable, optional): A function to load a sample given its path.
        extensions (tuple[string], optional): A list of allowed extensions.
            both extensions and is_valid_file should not be passed.
        transform (callable, optional): A function/transform that takes in
            a sample and returns a transformed version.
        is_valid_file (callable, optional): A function that takes path of a file
            and check if the file is a valid file (used to check of corrupt files)
            both extensions and is_valid_file should not be passed.

     Attributes:
        samples (list): List of sample path

    Example:

        .. code-block:: python

            import os
            import cv2
            import tempfile
            import shutil
            import numpy as np
228
            from paddle.vision.datasets import ImageFolder
229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300

            def make_fake_dir():
                data_dir = tempfile.mkdtemp()

                for i in range(2):
                    sub_dir = os.path.join(data_dir, 'class_' + str(i))
                    if not os.path.exists(sub_dir):
                        os.makedirs(sub_dir)
                    for j in range(2):
                        fake_img = (np.random.random((32, 32, 3)) * 255).astype('uint8')
                        cv2.imwrite(os.path.join(sub_dir, str(j) + '.jpg'), fake_img)
                return data_dir

            temp_dir = make_fake_dir()
            data_folder = ImageFolder(temp_dir)

            for items in data_folder:
                break
                
            shutil.rmtree(temp_dir)
     """

    def __init__(self,
                 root,
                 loader=None,
                 extensions=None,
                 transform=None,
                 is_valid_file=None):
        self.root = root
        if extensions is None:
            extensions = IMG_EXTENSIONS

        samples = []
        path = os.path.expanduser(root)

        if extensions is not None:

            def is_valid_file(x):
                return has_valid_extension(x, extensions)

        for root, _, fnames in sorted(os.walk(path, followlinks=True)):
            for fname in sorted(fnames):
                f = os.path.join(root, fname)
                if is_valid_file(f):
                    samples.append(f)

        if len(samples) == 0:
            raise (RuntimeError(
                "Found 0 files in subfolders of: " + self.root + "\n"
                "Supported extensions are: " + ",".join(extensions)))

        self.loader = cv2_loader if loader is None else loader
        self.extensions = extensions
        self.samples = samples
        self.transform = transform

    def __getitem__(self, index):
        """
        Args:
            index (int): Index

        Returns:
            tuple: (sample, target) where target is class_index of the target class.
        """
        path = self.samples[index]
        sample = self.loader(path)
        if self.transform is not None:
            sample = self.transform(sample)
        return [sample]

    def __len__(self):
        return len(self.samples)