Instructions to use PaddlePaddle/SLANet_plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PaddleOCR
How to use PaddlePaddle/SLANet_plus with PaddleOCR:
# 1. See https://www.paddlepaddle.org.cn/en/install to install paddlepaddle # 2. pip install paddleocr from paddleocr import TableStructureRecognition model = TableStructureRecognition(model_name="SLANet_plus") output = model.predict(input="path/to/image.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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3fd52a23b0a0f8504bf75ce6a00be4071faeb78b06c9b4d700bfcedb823f4a8
- Size of remote file:
- 7.67 MB
- SHA256:
- 012986b0e2bfe90410618bfb4b7cf4fcb6c978caefd84c63c2934f8387b09ab8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.