| import datasets | |
| _CITATION = """\ | |
| @InProceedings{huggingface:dataset, | |
| title = {Small image-text set}, | |
| author={James Briggs}, | |
| year={2022} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| Demo dataset for testing or showing image-text capabilities. | |
| """ | |
| _HOMEPAGE = "https://huggingface.co/datasets/jamescalam/image-text-demo" | |
| _LICENSE = "" | |
| _REPO = "https://huggingface.co/datasets/jamescalam/image-text-demo" | |
| class ImageSet(datasets.GeneratorBasedBuilder): | |
| """Small sample of image-text pairs""" | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| 'text': datasets.Value("string"), | |
| 'image': datasets.Image(), | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| images_archive = dl_manager.download(f"{_REPO}/resolve/main/images.tgz") | |
| image_iters = dl_manager.iter_archive(images_archive) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "images": image_iters | |
| } | |
| ), | |
| ] | |
| def _generate_examples(self, images): | |
| """ This function returns the examples in the raw (text) form.""" | |
| for idx, (filepath, image) in enumerate(images): | |
| description = filepath.split('/')[-1][:-4] | |
| description = description.replace('_', ' ') | |
| yield idx, { | |
| "image": {"path": filepath, "bytes": image.read()}, | |
| "text": description, | |
| } | |