| --- |
| license: apache-2.0 |
| task_categories: |
| - image-to-text |
| language: |
| - en |
| tags: |
| - document |
| - code |
| - RAW-PDFs |
| - ocr |
| - pdf |
| - text |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # Openpdf-Analysis-Recognition |
|
|
| The **Openpdf-Analysis-Recognition** dataset is curated for tasks related to image-to-text recognition, particularly for scanned document images and OCR (Optical Character Recognition) use cases. It contains over 6,900 images in a structured `imagefolder` format suitable for training models on document parsing, PDF image understanding, and layout/text extraction tasks. |
|
|
| | **Attribute** | **Value** | |
| |---------------|------------------------| |
| | Task | Image-to-Text | |
| | Modality | Image | |
| | Format | ImageFolder | |
| | Language | English | |
| | License | Apache 2.0 | |
| | Size | 1K - 10K samples | |
| | Split | train (6,910 samples) | |
|
|
|
|
| ### Key Features |
|
|
| * Contains **6.91k** training samples of document-style images. |
| * Each sample is an **image**, with no associated text or label (raw OCR input). |
| * Dataset is auto-converted to **Parquet** format by Hugging Face for efficient streaming and processing. |
| * Suitable for OCR research, PDF document parsing, and code/text recognition tasks. |
|
|
| ## Usage |
|
|
| You can load the dataset using the Hugging Face `datasets` library: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("prithivMLmods/Openpdf-Analysis-Recognition") |
| ``` |
|
|
| ## File Size |
|
|
| * **Total download size**: \~2.72 GB |
| * **Auto-converted Parquet size**: \~2.71 GB |
|
|
| ## License |
|
|
| This dataset is released under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0). |
