prithivMLmods/Camel-Doc-OCR-080125
Image-Text-to-Text
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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:
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.
- Downloads last month
- 259
Size of downloaded dataset files:
2.72 GB
Size of the auto-converted Parquet files:
2.71 GB
Number of rows:
6,910
