metadata
tags:
- ocr
- text-recognition
- tesseract
- uv-script
- generated
dataset_info:
config_name: pp-ocrv6
features:
- name: image
dtype: image
- name: b_number
dtype: string
- name: page_index
dtype: int64
- name: source_row
dtype: int64
- name: markdown
dtype: string
- name: pp_ocr_blocks
dtype: string
- name: inference_info
dtype: string
splits:
- name: train
num_bytes: 20968020
num_examples: 50
download_size: 20577145
dataset_size: 20968020
configs:
- config_name: pp-ocrv6
data_files:
- split: train
path: pp-ocrv6/train-*
Document OCR using Tesseract
This dataset contains OCR results from images in davanstrien/moh-bench-sample using Tesseract, the classical open-source CPU OCR engine — a cheap, no-GPU baseline alongside the VLM OCR recipes.
Processing Details
- Source Dataset: davanstrien/moh-bench-sample
- Engine: Tesseract
5.3.0 - Language(s):
eng - Number of Samples: 50
- Processing Time: 0.5 min
- Processing Date: 2026-07-08 16:38 UTC
Configuration
- Image Column:
image - Output Column:
markdown - Dataset Split:
train - Page Segmentation Mode (psm): 3
- OCR Engine Mode (oem): 3
- Workers: 64
Model Information
Tesseract is a classical (non-VLM) OCR engine:
- Runs on CPU — no GPU required
- v4+ uses an LSTM-based recognition engine
- 100+ languages via installable data packs
- Plain-text output (no markdown / table / formula structure)
- Apache-2.0 licensed
Dataset Structure
The dataset contains all original columns plus:
markdown: The recognised text (plain text)inference_info: JSON list tracking all OCR models applied to this dataset
Reproduction
uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/tesseract-ocr.py \
davanstrien/moh-bench-sample \
<output-dataset> \
--image-column image \
--lang eng \
--psm 3
Generated with UV Scripts