Datasets:
				
			
			
	
			
			
	
		
		metadata
			license: apache-2.0
task_categories:
  - image-to-text
language:
  - en
tags:
  - document
  - code
  - RAW-PDFs
  - ocr
  - pdf
  - text
  - doc
  - finance
  - docvl
size_categories:
  - 1K<n<10K
OpenDoc-Null-6K
The OpenDoc-Null-6K 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/OpenDoc-Null-6K")
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.
