Datasets:

mehdigououiad
/

permis-ocr-ppocrv6

id stringclasses 2 values	side stringclasses 2 values	image imagewidth (px) 576 576	markdown stringclasses 2 values	pp_ocr_blocks stringclasses 2 values	inference_info stringclasses 1 value
permis-recto	recto		CAN 373473 as PERMIS DE CONDUIRE ROYAUME DU MA jeuues Prénom MEHDI Nom GOUOUIAD C.N.I. BE899456 .9.0 Né(e) le 24/02/1998 CASABLANCA Permis N° 02/567609 Casa nord le 20109/2016	[{"text": "", "score": 0.0, "bbox": [[508.0, 0.0], [525.0, 0.0], [516.0, 55.0], [499.0, 52.0]]}, {"text": "CAN 373473", "score": 0.9500215649604797, "bbox": [[523.0, 42.0], [573.0, 50.0], [571.0, 65.0], [520.0, 57.0]]}, {"text": "", "score": 0.0, "bbox": [[79.0, 486.0], [163.0, 486.0], [163.0, 503.0], [79.0, 503.0]]}, ...	[{"model_id": "PaddlePaddle/PP-OCRv6_medium", "det_model": "PP-OCRv6_medium_det", "rec_model": "PP-OCRv6_medium_rec", "tier": "medium", "params": "34.5M (22M det + 19M rec)", "rec_accuracy_pct": 83.2, "languages": "50 languages (zh, zh-Hant, en, ja + 46 Latin-script)", "engine": "paddle_static", "column_name": "markdow...
permis-verso	verso		CAN 373473 Catégories Date de délivrance Restrictions A1 A B 20/09/2016 C EB EC ED Date de in de validité05/10/20269100 0500 0408.1583	[{"text": "CAN 373473", "score": 0.980610191822052, "bbox": [[491.0, 137.0], [537.0, 145.0], [534.0, 159.0], [488.0, 151.0]]}, {"text": "", "score": 0.0, "bbox": [[82.0, 505.0], [122.0, 505.0], [122.0, 519.0], [82.0, 519.0]]}, {"text": "", "score": 0.0, "bbox": [[148.0, 503.0], [204.0, 503.0], [204.0, 520.0], [148.0, 5...	[{"model_id": "PaddlePaddle/PP-OCRv6_medium", "det_model": "PP-OCRv6_medium_det", "rec_model": "PP-OCRv6_medium_rec", "tier": "medium", "params": "34.5M (22M det + 19M rec)", "rec_accuracy_pct": 83.2, "languages": "50 languages (zh, zh-Hant, en, ja + 46 Latin-script)", "engine": "paddle_static", "column_name": "markdow...

OCR with PP-OCRv6 Medium

Plain-text OCR results for images from mehdigououiad/permis-ocr-bench, produced by PaddlePaddle's PP-OCRv6 medium pipeline (34.5M (22M det + 19M rec)).

Processing details

Source: mehdigououiad/permis-ocr-bench
Model: PP-OCRv6_medium (PP-OCRv6_medium_det + PP-OCRv6_medium_rec)
Tier: medium (34.5M (22M det + 19M rec))
Recognition accuracy: 83.2%
Languages: 50 languages (zh, zh-Hant, en, ja + 46 Latin-script)
Engine: paddle_static
Samples: 2
Processing time: 0.32 min
Processing date: 2026-08-11 13:49 UTC
License: Apache 2.0 (models)

Schema

Each row contains the original columns plus:

markdown: Plain text extracted from the image (reading-order concatenation of detected text lines, newline-separated).
pp_ocr_blocks: JSON list, one dict per detected text line:
```
[
  {
    "text": "recognized text",
    "score": 0.987,
    "bbox": [[x1, y1], [x2, y2], [x3, y3], [x4, y4]]
  }
]
```
score is the recognition confidence and bbox is the detection polygon (4-point quadrilateral in input-image pixel coordinates).
inference_info: JSON list tracking every model applied to this dataset.

Note: PP-OCRv6 is a classical detection+recognition pipeline, not a VLM. It outputs plain text rather than markdown. Per-line bounding boxes and confidence scores are available in pp_ocr_blocks.

Usage

import json
from datasets import load_dataset

ds = load_dataset("mehdigououiad/permis-ocr-ppocrv6", split="train")
print(ds[0]["markdown"])
for block in json.loads(ds[0]["pp_ocr_blocks"]):
    print(block["text"], block["score"])

Reproduction

hf jobs uv run --flavor t4-small -s HF_TOKEN \
    https://huggingface.co/datasets/uv-scripts/ocr/raw/main/pp-ocrv6.py \
    mehdigououiad/permis-ocr-bench <output> --model-tier medium

Generated with UV Scripts.

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