---
tags:
- ocr
- text-recognition
- paddleocr
- pp-ocrv6
- uv-script
- generated
dataset_info:
  config_name: unlimited-ocr
  features:
  - name: image
    dtype: image
  - name: volume
    dtype: int64
  - name: volume_label
    dtype: string
  - name: leaf_number
    dtype: int64
  - name: page_number
    dtype: string
  - name: page_number_confidence
    dtype: int64
  - name: page_type
    dtype: string
  - name: width
    dtype: int64
  - name: height
    dtype: int64
  - name: ocr_text
    dtype: string
  - name: markdown
    dtype: string
  - name: inference_info
    dtype: string
  splits:
  - name: train
    num_bytes: 843256
    num_examples: 5
  download_size: 848759
  dataset_size: 843256
configs:
- config_name: unlimited-ocr
  data_files:
  - split: train
    path: unlimited-ocr/train-*
---

# OCR with PP-OCRv6 Medium

Plain-text OCR results for images from [davanstrien/encyclopaedia-britannica-1771](https://huggingface.co/datasets/davanstrien/encyclopaedia-britannica-1771), produced by
PaddlePaddle's [PP-OCRv6](https://huggingface.co/collections/PaddlePaddle/pp-ocrv6)
medium pipeline (34.5M (22M det + 19M rec)).

## Processing details

- **Source**: [davanstrien/encyclopaedia-britannica-1771](https://huggingface.co/datasets/davanstrien/encyclopaedia-britannica-1771)
- **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**: 5
- **Processing time**: 0.82 min
- **Processing date**: 2026-07-07 23:06 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:
  ```json
  [
    {
      "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

```python
import json
from datasets import load_dataset

ds = load_dataset("davanstrien/ocr-bench-smoke", split="train")
print(ds[0]["markdown"])
for block in json.loads(ds[0]["pp_ocr_blocks"]):
    print(block["text"], block["score"])
```

## Reproduction

```bash
hf jobs uv run --flavor t4-small -s HF_TOKEN \
    https://huggingface.co/datasets/uv-scripts/ocr/raw/main/pp-ocrv6.py \
    davanstrien/encyclopaedia-britannica-1771 <output> --model-tier medium
```

Generated with [UV Scripts](https://huggingface.co/uv-scripts).