omnidocbench
OmniDocBench
OmniDocBench
English | 简体中文
OmniDocBench is an evaluation dataset for diverse document parsing in real-world scenarios, with the following characteristics:
Diverse Document Types: The evaluation set contains 1651 PDF pages, covering 10 document types, 5 layout types and 5 language types. Coverage includes academic literature, research and financial reports, newspapers, textbooks, exam papers, magazines, handwritten notes, historical documents, and more.
Rich Annotations:… See the full description on the dataset page: https://huggingface.co/datasets/opendatalab/OmniDocBench.Real5-OmniDocBench
Real5-OmniDocBench
A Full-Scale Physical Reconstruction Benchmark for Robust Document Parsing in the Wild
Leaderboard | Overview | Dataset | Evaluation | Submit Results | Citation
Real5-OmniDocBench measures the robustness of document parsing systems under five physical acquisition conditions: Scanning, Warping, Screen-Photography, Illumination, and Skew. It reconstructs the same 1,355 pages from OmniDocBench v1.5 in every condition, producing 6,775 images in total. The one-to-one… See the full description on the dataset page: https://huggingface.co/datasets/PaddlePaddle/Real5-OmniDocBench.OmniDocBenchForked from opendatalab/OmniDocBench.
Sampler
We have added a simple Python tool for filtering and performing stratified sampling on OmniDocBench data.
Features
Filter JSON entries based on custom criteria
Perform stratified sampling based on multiple categories
Handle nested JSON fields
Installation
Local Development Install (Recommended)
git clone https://huggingface.co/Quivr/OmniDocBench.git
cd OmniDocBench
pip install -r requirements.txt #… See the full description on the dataset page: https://huggingface.co/datasets/Quivr/OmniDocBench.omnidocbench
OmniDocBench
English | 简体中文
OmniDocBench is an evaluation dataset for diverse document parsing in real-world scenarios, with the following characteristics:
Diverse Document Types: The evaluation set contains 981 PDF pages, covering 9 document types, 4 layout types and 3 language types. It has broad coverage including academic papers, financial reports, newspapers, textbooks, handwritten notes, etc.
Rich Annotations: Contains location information for 15 block-level (text paragraphs… See the full description on the dataset page: https://huggingface.co/datasets/samiuc/omnidocbench.omnidocbench-render-compare
OmniDocBench Render-and-Compare
This dataset contains the rendered HTML reconstructions and comparison images produced
by a render-and-compare pipeline — a reference-free visual similarity evaluation
framework for OCR systems.
Overview
The pipeline processes each page of OmniDocBench through
a Qwen3.5-122B-A10B OCR model, renders the structured output back to a PNG via HTML
(reconstructed.png), and compares it against the original page scan (masked_original.png)
using… See the full description on the dataset page: https://huggingface.co/datasets/gt-free-ocr-metrics/omnidocbench-render-compare.OmniDocBench_tsvThis repository contains the TSV version of the ground truth data for OmniDocBench, , converted from the dataset available at opendatalab/OmniDocBench.
Note: The main branch now corresponds to version v1_0 of the OmniDocBench ground truth.