"""Kodak.

Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.

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 datasets

NUMBER = 24
_DESCRIPTION = """\
The pictures below link to lossless, true color (24 bits per pixel, aka "full
color") images. It is my understanding they have been released by the Eastman
Kodak Company for unrestricted usage. Many sites use them as a standard test
suite for compression testing, etc. Prior to this site, they were only
available in the Sun Raster format via ftp. This meant that the images could
not be previewed before downloading. Since their release, however, the lossless
PNG format has been incorporated into all the major browsers. Since PNG
supports 24-bit lossless color (which GIF and JPEG do not), it is now possible
to offer this browser-friendly access to the images.
"""
_HOMEPAGE = "https://r0k.us/graphics/kodak/"
_LICENSE = "GPLv3"
_URLS = [
    f"https://github.com/MohamedBakrAli/Kodak-Lossless-True-Color-Image-Suite/raw/master/PhotoCD_PCD0992/{i}.png"
    for i in range(1, 1 + NUMBER)
]


class Kodak(datasets.GeneratorBasedBuilder):
    """Kodak datasets."""

    VERSION = datasets.Version("0.0.1")

    def _info(self):
        features = datasets.Features(
            {
                "image": datasets.Image(),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
        )

    def _split_generators(self, dl_manager):
        """Return SplitGenerators."""
        file_paths = dl_manager.download_and_extract(_URLS)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "file_paths": file_paths,
                },
            ),
        ]

    def _generate_examples(self, file_paths):
        """Yield examples."""
        for file_path in file_paths:
            yield file_path, {"image": file_path}