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PaddlePaddle/PP-DocBlockLayout_onnx

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face
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Model Card

PP-DocBlockLayout

Introduction

A layout block localization model trained on a self-built dataset containing Chinese and English papers, PPT, multi-layout magazines, contracts, books, exams, ancient books and research reports using RT-DETR-L. The layout detection model includes 1 category: Region.

ModelmAP(0.5) (%)
PP-DocBlockLayout95.9

Note: the evaluation set of the above precision indicators is the self built version sub area detection data set, including Chinese and English papers, magazines, newspapers, research reports PPT、 1000 document type pictures such as test papers and textbooks.

Model Usage

Install Dependencies

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

CLI Usage

shell
paddleocr layout_detection -i ./demo.jpg --model_name PP-DocBlockLayout --engine onnxruntime

Python API Usage

python
from paddleocr import LayoutDetection

model = LayoutDetection(
    model_name="PP-DocBlockLayout",
    engine="onnxruntime",
)
output = model.predict("./demo.jpg", 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")