---
license: apache-2.0
tags:
- libreyolo
- ocr
- text-detection
- text-recognition
- pp-ocr
---

# LibrePPOCRl-ocr

PP-OCRv5 server tier (quality tier) converted to the LibreYOLO checkpoint
format: one composite `.pt` bundling the DB text detector (`det.*`) and the
CTC text recognizer (`rec.*`) plus the PP-OCRv5 recognition dictionary as
`charset` metadata. Recognition covers Simplified Chinese, Traditional
Chinese, English, Japanese, and Chinese pinyin with one dictionary and one
model.

```python
from libreyolo import LibreYOLO

model = LibreYOLO("LibrePPOCRl-ocr.pt")
r = model("receipt.jpg")
for poly, text, conf in zip(r.ocr.polygons, r.ocr.texts, r.ocr.conf):
    print(text, float(conf))
```

## Provenance

Converted with `weights/convert_ppocr_weights.py` from the official Apache-2.0
PP-OCRv5 training checkpoints released by the
[PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) project
(paper: [PaddleOCR 3.0 Technical Report](https://arxiv.org/abs/2507.05595)):

| Upstream checkpoint | SHA-256 |
|---|---|
| `PP-OCRv5_server_det_pretrained.pdparams` | `2802f7d4748ea592819ae4550c195c5bdb43755dfdb5ebd25e01bb4d885aebc9` |
| `PP-OCRv5_server_rec_pretrained.pdparams` | `8ce5dfc1294af6ee680d562841a9909257d6a9a9242387c2e8dc50ea8f647143` |

This file: `LibrePPOCRl-ocr.pt`, SHA-256
`6a58b6a2af947a40d48e50c2aa2f050b300d10367bdba5840993b900bf59358e`.

The conversion is a name-mapped metadata wrap (batch-norm buffer renames,
Linear transposes, `det.`/`rec.` namespacing); learned parameters are
unchanged. Stage parity vs the official PP-OCRv5 inference graphs on
identical input tensors: detection maps match to <= 1e-4 and recognition
probabilities to <= 6e-5 with identical argmax.

Code and weights are used under the
[Apache License 2.0](http://www.apache.org/licenses/LICENSE-2.0).
Copyright (c) 2020 PaddlePaddle Authors.