| import os |
| import pandas as pd |
| import datasets |
| import json |
| from huggingface_hub import hf_hub_url |
|
|
| _INPUT_CSV = 'captions.txt' |
| _INPUT_IMAGES = "Images" |
| _REPO_ID = "shivangibithel/flickr8k" |
| _JSON_KEYS = ['caption'] |
|
|
| class Dataset(datasets.GeneratorBasedBuilder): |
| VERSION = datasets.Version("1.1.0") |
| BUILDER_CONFIGS = [ |
| datasets.BuilderConfig(name="ALL", version=VERSION, description="all"), |
| ] |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| features=datasets.Features( |
| { |
| "image": datasets.Image(), |
| "caption": [datasets.Value('string')], |
| "image_filename": datasets.Value("string"), |
| } |
| ), |
| task_templates=[], |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| """Returns SplitGenerators.""" |
|
|
| repo_id = _REPO_ID |
| data_dir = dl_manager.download_and_extract({ |
| "examples_csv": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=_INPUT_CSV), |
| "images_dir": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=f"{_INPUT_IMAGES}.zip") |
| }) |
|
|
| return [datasets.SplitGenerator(name=datasets.Split.ALL, gen_kwargs=data_dir)] |
|
|
|
|
| def _generate_examples(self, examples_csv, images_dir): |
| """Yields examples.""" |
| df = pd.read_csv(examples_csv, delimiter=',') |
| for c in _JSON_KEYS: |
| df[c] = df[c].apply(json.loads) |
|
|
| for r_idx, r in df.iterrows(): |
| r_dict = r.to_dict() |
| image_path = os.path.join(images_dir, _INPUT_IMAGES, r_dict['image_filename']) |
| r_dict['image'] = image_path |
| r_dict['caption'] = r_dict.pop('caption') |
| yield r_idx, r_dict |