PP OCRv5 Mobile Rec Onnx
PP-OCRv5mobilerec is one of the PP-OCRv5rec that are the latest generation text line recognition models developed by PaddleOCR team. It aims to efficiently and accurately support the recognition of four major...
Fuente del modelo
- Tipo
- Modelo
- Tamaño del archivo
- 15,8 MB
- Versión
- vRevision ed152b8
- Actualizado
- 30 oct 2026
- Descargas
- 9,5 mil
- Fuente
- Hugging Face
Descripción de la fuente
PP-OCRv5_mobile_rec
Introduction
PP-OCRv5_mobile_rec is one of the PP-OCRv5_rec that are the latest generation text line recognition models developed by PaddleOCR team. It aims to efficiently and accurately support the recognition of four major languages—Simplified Chinese, Traditional Chinese, English, and Japanese—as well as complex text scenarios such as handwriting, vertical text, pinyin, and rare characters using a single model. The key accuracy metrics are as follow:
| Handwritten Chinese | Handwritten English | Printed Chinese | Printed English | Traditional Chinese | Ancient Text | Japanese | General Scenario | Pinyin | Rotation | Distortion | Artistic Text | Average |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4166 | 0.4944 | 0.8605 | 0.8753 | 0.7199 | 0.5786 | 0.7577 | 0.5570 | 0.7703 | 0.7248 | 0.8089 | 0.5398 | 0.8015 |
Note: If any character (including punctuation) in a line is incorrect, the entire line is marked as wrong. This ensures higher accuracy in practical applications.
Model Usage
Install Dependencies
pip install -U paddleocr
pip install -U onnxruntime-gpu
CLI Usage
paddleocr text_recognition -i ./demo.png --model_name PP-OCRv5_mobile_rec --engine onnxruntime
Python API Usage
from paddleocr import TextRecognition
model = TextRecognition(
model_name="PP-OCRv5_mobile_rec",
engine="onnxruntime",
)
output = model.predict("./demo.png", batch_size=1)
for res in output:
res.print()
res.save_to_json(save_path="./output/res.json")
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 30 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- license: apache-2.0 library_name: PaddleOCR language: - en - zh pipeline_tag: image-to-text tags: - OCR - PaddlePaddle - PaddleOCR - textline_recognition --- # PP-OCRv5_mobile_rec ## Introduction PP-OCRv5_mobile_rec is one of the PP-OCRv5_rec that are the latest generation text line recognition models developed by PaddleOCR team. It aims to efficiently and accurately support the recognition of four major languages—Simplified Chinese, Traditional Chinese, English, and Japanese—as well as complex text scenarios such as handwriting, vertical text, pinyin, and rare characters using a single model. The key accuracy metrics are as follow: | Handwritten Chinese | Handwritten English | Printed Chinese | Printed English | Traditional Chinese | Ancient Text | Japanese | General Scenario | Pinyin | Rotation | Distortion | Artistic Text | Average | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 0.4166 | 0.4944 | 0.8605 | 0.8753 | 0.7199 | 0.5786 | 0.7577 | 0.5570 | 0.7703 | 0.7248 | 0.8089 | 0.5398 | 0.8015 | **Note**: If any character (including punctuation) in a line is incorrect, the entire line is marked as wrong. This ensures higher accuracy in practical applications. ## Model Usage ### Install Dependencies ```shell pip install -U paddleocr pip install -U onnxruntime-gpu ``` ### CLI Usage ```shell paddleocr text_recognition -i ./demo.png --model_name PP-OCRv5_mobile_rec --engine onnxruntime ``` ### Python API Usage ```python from paddleocr import TextRecognition model = TextRecognition( model_name="PP-OCRv5_mobile_rec", engine="onnxruntime", ) output = model.predict("./demo.png", batch_size=1) for res in output: res.print() res.save_to_json(save_path="./output/res.json") ```
Source context: 9450 downloads · 0 likes · Pipeline image-to-text · Library PaddleOCR · Repo PaddlePaddle/PP-OCRv5_mobile_rec_onnx
Source context: 2767 downloads · 0 likes · Pipeline image-to-text · Library PaddleOCR · Repo PaddlePaddle/PP-OCRv5_mobile_rec_onnx
