Linear Transformer for Table Recognition

Introduction

This is the code repository for participation in ICDAR2021 Competition on scientific literature parsing - Task B: Table recognition (Team Name: LTIAYN = Kaen Context).

• Dataset: PubTabNet
• Metric: Tree-Edit-Distance-based Similarity(TEDS)
• Baseline: Image-based table recognition: data, model, and evaluation

0. Before Training

1. change the prefined data directory '/data/private/datasets/pubtabnet' to your own data directory in 'processing_pubtabnet.py', 'configs/linear_transformer.yaml'
2. python processing_pubtabnet.py

1. Training

python train.py model_dir=base

2. After Training

1. inference

python inference.py -m "./outputs/base/" -i "/data/private/datasets/pubtabnet/val/" -o "./results/val1" -nt 16 -ni 0 -na 20
python inference.py -m "./outputs/base/" -i "/data/private/datasets/pubtabnet/val/" -o "./results/val1" -nt 16 -ni 1 -na 20
...
python inference.py -m "./outputs/base/" -i "/data/private/datasets/pubtabnet/val/" -o "./results/val1" -nt 16 -ni 15 -na 20

2. evalution

python score.py