| # coding=utf-8 | |
| # 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.Wikipedia | |
| # Lint as: python3 | |
| """Dream!n character datasets""" | |
| import datasets | |
| _CITATION = """ | |
| """ | |
| _DESCRIPTION = "Dream!n character datasets" | |
| _DATASET_URL = "https://huggingface.co/datasets/JAWCF/character-demo/resolve/main/images.tar.gz" | |
| class Characters(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| features = datasets.Features({ | |
| 'image': datasets.Image(), | |
| 'text': datasets.Value('string') | |
| }) | |
| return datasets.DatasetInfo( | |
| # This is the description that will appear on the datasets page. | |
| description=_DESCRIPTION, | |
| # This defines the different columns of the dataset and their types | |
| features=features, # Here we define them above because they are different between the two configurations | |
| supervised_keys=None, | |
| # Homepage of the dataset for documentation | |
| homepage="", | |
| # License for the dataset if available | |
| license="", | |
| # Citation for the dataset | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| path = dl_manager.download(_DATASET_URL) | |
| image_iters = dl_manager.iter_archive(path) | |
| splits = [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "images": image_iters | |
| } | |
| ), | |
| ] | |
| return splits | |
| def _generate_examples(self, images): | |
| """Yields examples.""" | |
| for filepath, image in images: | |
| print(filepath) | |
| yield { | |
| "image": {"path": filepath, "bytes": image.read()}, | |
| "text" : "alal", | |
| } |