PP-OCRv5_mobile_det

Introduction

PP-OCRv5_mobile_det is one of the PP-OCRv5_det series, the latest generation of text detection models developed by the PaddleOCR team. It aims to efficiently and accurately supports the detection of text in diverse scenarios—including handwriting, vertical, rotated, and curved text—across multiple languages such as Simplified Chinese, Traditional Chinese, English, and Japanese. Key features include robust handling of complex layouts, varying text sizes, and challenging backgrounds, making it suitable for practical applications like document analysis, license plate recognition, and scene text detection. 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
0.744	0.777	0.905	0.910	0.823	0.581	0.727	0.721	0.575	0.647	0.827	0.525	0.770

Model Usage

Install Dependencies

pip install -U paddleocr
pip install -U onnxruntime-gpu

CLI Usage

paddleocr text_detection -i ./demo.png --model_name PP-OCRv5_mobile_det --engine onnxruntime

Python API Usage

from paddleocr import TextDetection

model = TextDetection(
    model_name="PP-OCRv5_mobile_det",
    engine="onnxruntime",
)
output = model.predict("./demo.png", batch_size=1)
for res in output:
    res.print()
    res.save_to_img(save_path="./output/")
    res.save_to_json(save_path="./output/res.json")