Table_Ocr_With_Paddle

This is the Table extraction model in which you just turn an image of a table and turned it into the csv.

This is not use to detect the table in the paper.

Baseline	BLEU-A	BLEU-1	BLEU-2	BLEU-3	BLEU-4	ROUGE-LCSF1	FIELD8
ast-attendgru	18.69	37.13	21.11	14.27	10.90	49.75
graph2seq	18.61	37.56	21.27	14.13	10.63	49.69
code2seq	18.84	37.49	21.36	14.37	10.95	49.69
BiLSTM+GNN-iLSTM	19.05	37.70	21.53	14.59	11.11	55.74
ConvGNNModels	#of hops	BLEU-A	BLEU-1	BLEU-2	BLEU-3	BLEU-4	ROUGE-LCSF1
code+gnn+dense	2	19.46	38.71	22.04	14.86	11.31	56.07
code+gnn+BiLSTM	2	19.93	39.14	22.49	15.31	11.70	56.08
code+gnn+GRU	1	19.70	38.15	22.12	15.22	11.73	57.15
code+gnn+GRU	2	19.89	39.01	22.42	15.28	11.70	55.78
code+gnn+GRU	3	19.58	38.48	22.09	15.01	11.52	56.14
code+gnn+GRU	5	19.68	38.89	22.30	15.09	11.46	55.81
code+gnn+GRU	10	19.34	38.68	21.94	14.73	11.20	55.10

Dependent

All codes modified from the PaddlePaddle OCR, need to first setup paddlepaddle

QUICK INSTALL

Model

Download Model from PP-OCR and put it into the inference file

• Recognition model
• Detection model
• Direction classifier

./inference/
    ch_ppocr_mobile_v2.0_cls_infer/
    ch_ppocr_server_v2.0_det_infer/
    ch_ppocr_server_v2.0_rec_infer/

Use

sh infer_table.sh

After pops out the waiting line Extract Table From Image ("?"/"h" for help,"x" for exit)

Just use your Screenshots tools to cut an image in the clipboard and input enter. You will see the final result in the ./example.csv and the screenshot as pic.png

OR use it with local image --image_dir=''

python3  tools/infer/predict_table.py --clipboard False --image_dir='pic.png' --det_model_dir="./inference/ch_ppocr_server_v2.0_det_infer/"  --rec_model_dir="./inference/ch_ppocr_server_v2.0_rec_infer/"  --cls_model_dir="./inference/ch_ppocr_mobile_v2.0_cls_infer/"  --use_angle_cls=True --use_space_char=True --use_gpu=False