PaddlePaddle/PP-OCRv5_server_rec_onnx

PP-OCRv5_server_rec

Introduction

PP-OCRv5_server_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
0.5807	0.5806	0.9013	0.8679	0.7472	0.6039	0.7372	0.5946	0.8384	0.7435	0.9314	0.6397	0.8401

Note: If any character (including punctuation) in a line was incorrect, the entire line was 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_server_rec --engine onnxruntime

Python API Usage

from paddleocr import TextRecognition

model = TextRecognition(
    model_name="PP-OCRv5_server_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")