Datasets:

minhpvo
/

ocr-output_paddleocr_ocr

filename stringlengths 7 7	paddleocr_ocr stringlengths 16 16.4k	inference_info stringclasses 1 value
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002.jpg	OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFERENCE OVERALL DIFFEREN...	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
003.jpg	Sample House Street Address City, ST Zip (NY) SHEET SEE 54 16 341 A3	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
004.jpg	Sample House street Address city, ST Zip (744) 587-5514 x 347	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
005.jpg	Sample House Street Address City, ST Zip	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
006.jpg	Glazing Area 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0...	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
007.jpg	A7 Date: Month: Day: Date: Month: Day: SETT NUMBER SETT TITLE SETT NUMBER SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT TITLE SETT...	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
008.jpg	LEGAL DESCRIPTION LOT COVERAGE AVERAGE BUILDING ELEVATION GENERAL NOTES PROJECT TEAM DATE, Month-Day, Year (M/A SHEET 55/A 1/A) SHEET NUMBER SHEET TITLE SITE PLAN LEGEND SITE PLAN LEGEND SITE PLAN LEGEND SITE PLAN LEGEND SITE PLAN LEGEND SITE PLAN LEGEND SITE PLAN LEGEND SITE PLAN LEGEND SITE PLAN LEGEND SITE PLAN LEGE...	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
009.png	Half-Planet: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ecliptic: Half-Ec...	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
010.png	Half Plan at Top Half Plan at Bottom Half Plan at Bottom Half Plan at Top Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half Plan at Bottom Half P...	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
011.png	OF WING WALL @ MAX. HEIGHT C/S OF WING WALL @ MIN. HEIGHT SAF MA	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
012.png	2020-01-01 2020-01-02 2020-01-03 2020-01-04 2020-01-05 2020-01-06 2020-01-07 2020-01-08 2020-01-09 2020-01-10 2020-01-11 2020-01-12 2020-01-13 2020-01-14 2020-01-15 2020-01-16 2020-01-17 2020-01-18 2020-01-19 2020-01-20 2020-01-21 2020-01-22 2020-01-23 2020-01-24 2020-01-25 2020-01-26 2020-01-27 2020-01-28 2020-01-29 2...	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]
013.png	FIRST FLOOR PLAN	[{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "ocr", "column_name": "paddleocr_ocr", "timestamp": "2026-02-09T03:59:38.431667", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}]

Document Processing using PaddleOCR-VL (OCR mode)

This dataset contains OCR results from images in minhpvo/ocr-input using PaddleOCR-VL, an ultra-compact 0.9B OCR model.

Processing Details

Source Dataset: minhpvo/ocr-input
Model: PaddlePaddle/PaddleOCR-VL
Task Mode: ocr - General text extraction to markdown format
Number of Samples: 13
Processing Time: 1.9 min
Processing Date: 2026-02-09 03:59 UTC

Configuration

Image Column: image
Output Column: paddleocr_ocr
Dataset Split: train
Batch Size: 16
Smart Resize: Enabled
Max Model Length: 8,192 tokens
Max Output Tokens: 4,096
Temperature: 0.0
GPU Memory Utilization: 80.0%

Model Information

PaddleOCR-VL is a state-of-the-art, resource-efficient model tailored for document parsing:

🎯 Ultra-compact - Only 0.9B parameters (smallest OCR model)
📝 OCR mode - General text extraction
📊 Table mode - HTML table recognition
📐 Formula mode - LaTeX mathematical notation
📈 Chart mode - Structured chart analysis
🌍 Multilingual - Support for multiple languages
⚡ Fast - Quick initialization and inference
🔧 ERNIE-4.5 based - Different architecture from Qwen models

Task Modes

OCR: Extract text content to markdown format
Table Recognition: Extract tables to HTML format
Formula Recognition: Extract mathematical formulas to LaTeX
Chart Recognition: Analyze and describe charts/diagrams

Dataset Structure

The dataset contains all original columns plus:

paddleocr_ocr: The extracted content based on task mode
inference_info: JSON list tracking all OCR models applied to this dataset

Usage

from datasets import load_dataset
import json

# Load the dataset
dataset = load_dataset("{output_dataset_id}", split="train")

# Access the extracted content
for example in dataset:
    print(example["paddleocr_ocr"])
    break

# View all OCR models applied to this dataset
inference_info = json.loads(dataset[0]["inference_info"])
for info in inference_info:
    print(f"Task: {info['task_mode']} - Model: {info['model_id']}")

Reproduction

This dataset was generated using the uv-scripts/ocr PaddleOCR-VL script:

uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/paddleocr-vl.py \
    minhpvo/ocr-input \
    <output-dataset> \
    --task-mode ocr \
    --image-column image \
    --batch-size 16 \
    --max-model-len 8192 \
    --max-tokens 4096 \
    --gpu-memory-utilization 0.8

Performance

Model Size: 0.9B parameters (smallest among OCR models)
Processing Speed: ~0.11 images/second
Architecture: NaViT visual encoder + ERNIE-4.5-0.3B language model

Generated with 🤖 UV Scripts

Downloads last month: 9

Size of downloaded dataset files:

16.3 MB

Size of the auto-converted Parquet files:

16.3 MB

Number of rows: