- To train a model run command like :
python3 train.py --train_data train --valid_data test --select_data / --batch_ratio 1 --Transformation TPS --FeatureExtraction ResNet --SequenceModeling BiLSTM --Prediction Attn --lr 0.0005 --adam --data_filtering_off --PAD --num_iter 1000000 --batch_size 64 --imgW 224 - For predicting on test set:
python3 predict.py --Transformation TPS --FeatureExtraction ResNet --SequenceModeling BiLSTM --Prediction Attn --model_path saved_models/TPS-ResNet-BiLSTM-Attn-Seed2020/best_accuracy.pth
--train_data: folder path to training lmdb dataset.--valid_data: folder path to validation lmdb dataset.--select_data: select training data.--batch_ratio: assign ratio for each selected data in the batch.--Transformation: select Transformation module [None | TPS].--FeatureExtraction: select FeatureExtraction module [VGG | RCNN | ResNet].--SequenceModeling: select SequenceModeling module [None | BiLSTM].--Prediction: select Prediction module [CTC | Attn].--saved_model: assign saved model to evaluation.
This repository is based on https://github.com/clovaai/deep-text-recognition-benchmark.