| --- |
| license: odc-by |
| language: |
| - en |
| pretty_name: OCR-Annotations |
| size_categories: |
| - n>1T |
| --- |
| |
|
|
|  |
|
|
| # PDF OCR Classification Dataset |
|
|
| This dataset contains PDF documents with annotations for OCR classification tasks. |
|
|
| ## Dataset Description |
|
|
| - **Total samples**: 1620 |
| - **Classes**: OCR (requires OCR processing), NOCR (no OCR needed) |
|
|
| ## Dataset Structure |
|
|
| Each row contains: |
| - `filename`: Original PDF filename |
| - `pdf`: PDF file as binary data (using Pdf feature type) |
| - `class`: Binary classification label (OCR/NOCR) |
| - `truncation_type`: Whether the PDF is truncated or non-truncated |
| - `pdf_size_bytes`: Size of the PDF file in bytes |
|
|
| ## Class Distribution |
|
|
| class |
| NOCR 1393 |
| OCR 227 |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load the dataset |
| dataset = load_dataset("HuggingFaceFW/ocr-annotations") |
| |
| # Access train split |
| train_data = dataset['train'] |
| |
| # Access a sample |
| sample = train_data[0] |
| pdf_bytes = sample['pdf'] # This will be bytes |
| label = sample['class'] |
| ``` |
|
|
| ## License |
|
|
| Please check the original data source for licensing information. |
|
|
