| import os | |
| import pandas as pd | |
| import zipfile | |
| import datasets | |
| from datasets import load_dataset | |
| class SyntheticCyrillic(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| features=datasets.Features( | |
| { | |
| "image": datasets.Image(), | |
| "text": datasets.Value("string"), | |
| "path": datasets.Value("string"), | |
| "name": datasets.Value("string") | |
| } | |
| ) | |
| ) | |
| def _split_generators(self, dl_manager): | |
| _URLS = {"img": "img.zip", "labels": "gt.txt"} | |
| data_paths = dl_manager.download_and_extract(_URLS) | |
| return [datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "image_paths": dl_manager.iter_files(data_paths["img"]), | |
| "labels_path": data_paths["labels"] | |
| })] | |
| def _generate_examples(self, image_paths, labels_path): | |
| df = pd.read_csv(labels_path, sep=",", names=["path", "text"]) | |
| df["path"] = df.path.str[4:] | |
| df.set_index("path", inplace=True) | |
| for image_path in image_paths: | |
| image_name = os.path.basename(image_path) | |
| if image_name in df.index: | |
| example = { | |
| "image": image_path, | |
| "text": df["text"][image_name], | |
| "path": image_path, | |
| "name": image_name | |
| } | |
| yield image_name, example | |