| Dataset derived from FUNSD for training GLiNER-based multi-modal models. | |
| Processing script: | |
| ```python | |
| from datasets import load_dataset | |
| import shutil | |
| import json | |
| import os | |
| dataset = load_dataset("nielsr/funsd") | |
| raw_labels = dataset['train'].features['ner_tags'].feature.names | |
| gliner_pdf_dataset = [] | |
| output_dir = "gliner_funsd" | |
| os.makedirs(output_dir, exist_ok=True) | |
| os.makedirs(os.path.join(output_dir, 'images'), exist_ok=True) | |
| def process_dataset(example): | |
| tokens = example['words'] | |
| bboxes = example['bboxes'] | |
| img_src = example['image_path'] | |
| ner_spans = [] | |
| prev_label = 'O' | |
| prev_idx = None | |
| for idx, tag_id in enumerate(example['ner_tags']): | |
| lbl = raw_labels[tag_id] | |
| if lbl == 'O': | |
| if prev_label != 'O': | |
| ner_spans.append([prev_idx, idx - 1, prev_label]) | |
| prev_label = 'O' | |
| continue | |
| _, label = lbl.split('-', 1) | |
| if prev_label != label: | |
| if prev_label != 'O': | |
| ner_spans.append([prev_idx, idx - 1, prev_label]) | |
| prev_idx = idx | |
| prev_label = label | |
| if prev_label != 'O': | |
| ner_spans.append([prev_idx, len(example['ner_tags']) - 1, prev_label]) | |
| fname = os.path.basename(img_src) | |
| img_dst = os.path.join(output_dir, 'images', fname) | |
| shutil.copy(img_src, img_dst) | |
| gliner_pdf_dataset.append({ | |
| "tokenized_text": tokens, | |
| "bboxes": bboxes, | |
| "ner": ner_spans, | |
| "image_path": img_dst | |
| }) | |
| for ex in dataset['train']: | |
| process_dataset(ex) | |
| with open(os.path.join(output_dir, 'data.json'), 'w') as f: | |
| json.dump(gliner_pdf_dataset, f) | |
| ``` |