Tools for document layout analysis based ONNXRuntime.
Project description
rapid-layout
1. Install package by pypi.
$ pip install rapid-layout
2. Run by script.
- RapidLayout has the default
model_pathvalue, you can set the different value ofmodel_pathto use different models, e.g.layout_engine = RapidLayout(model_path='layout_publaynet.onnx') - See details, for README_Layout .
- 📌
layout.pngsource: link
from rapid_layout import RapidLayout
layout_engine = RapidLayout()
with open('layout.png', 'rb') as f:
img = f.read()
layout_res, elapse = layout_engine(img)
print(layout_res)
3. Run by command line.
- Usage:
$ rapid_layout -h usage: rapid_layout [-h] [-v] -img IMG_PATH [-m MODEL_PATH] optional arguments: -h, --help show this help message and exit -v, --vis Wheter to visualize the layout results. -img IMG_PATH, --img_path IMG_PATH Path to image for layout. -m MODEL_PATH, --model_path MODEL_PATH The model path used for inference.
- Example:
$ rapid_layout -v -img layout.png
4. Result.
- Return value.
[ {'bbox': array([321.4160495, 91.53214898, 562.06141263, 199.85522603]), 'label': 'text'}, {'bbox': array([58.67292211, 107.29000663, 300.25448676, 199.68142]), 'label': 'table_caption'} ]
- Visualize result.
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