metadata

license: apache-2.0
task_categories:
  - image-to-text
language:
  - en
tags:
  - image
  - pdf
  - document
  - text
size_categories:
  - 1K<n<10K

OpenDoc-Pdf-Preview

OpenDoc-Pdf-Preview is a compact visual preview dataset containing 6,000 high-resolution document images extracted from PDFs. This dataset is designed for Image-to-Text tasks such as document OCR pretraining, layout understanding, and multimodal document analysis.

Dataset Summary

Modality: Image-to-Text
Content Type: PDF-based document previews
Number of Samples: 6,000
Language: English
Format: Parquet
Split: train only
Size: 606 MB
License: Apache 2.0

Each entry consists of:

A preview image of a PDF page
A placeholder column named pdf (currently appears empty or reserved for future metadata)

Use Cases

Pretraining OCR or Document Layout models
PDF snapshot-based search indexing
Few-shot document vision evaluation
Visual prompt tuning for vision-language models (VLMs)

How to Use

from datasets import load_dataset

dataset = load_dataset("prithivMLmods/OpenDoc-Pdf-Preview", split="train")

Notes

The column pdf may be extended in future versions with associated metadata or textual content.
Each sample preview is rendered from the original PDF file, representing various real-world layouts and formats.