Datasets:
Tasks:
Image-to-Text
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
License:
license: apache-2.0 | |
task_categories: | |
- image-to-text | |
language: | |
- en | |
tags: | |
- ocr | |
- document | |
- code | |
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). |