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support training progress bar #320

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support training progress bar #320

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2 changes: 1 addition & 1 deletion README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@ The difference between our paper and ICDAR challenge is summarized [here](https:
In the paper, expriments were performed with **PyTorch 0.4.1, CUDA 9.0**.
- requirements : lmdb, pillow, torchvision, nltk, natsort
```
pip3 install lmdb pillow torchvision nltk natsort
pip3 install lmdb pillow torchvision nltk natsort tqdm
```

### Download lmdb dataset for traininig and evaluation from [here](https://www.dropbox.com/sh/i39abvnefllx2si/AAAbAYRvxzRp3cIE5HzqUw3ra?dl=0)
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4 changes: 4 additions & 0 deletions train.py
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Expand Up @@ -11,6 +11,7 @@
import torch.optim as optim
import torch.utils.data
import numpy as np
from tqdm.auto import tqdm

from utils import CTCLabelConverter, CTCLabelConverterForBaiduWarpctc, AttnLabelConverter, Averager
from dataset import hierarchical_dataset, AlignCollate, Batch_Balanced_Dataset
Expand Down Expand Up @@ -142,6 +143,7 @@ def train(opt):
best_norm_ED = -1
iteration = start_iter

pbar = tqdm(total=opt.num_iter)
while(True):
# train part
image_tensors, labels = train_dataset.get_batch()
Expand Down Expand Up @@ -224,6 +226,8 @@ def train(opt):
print('end the training')
sys.exit()
iteration += 1
pbar.update(1)
pbar.close()


if __name__ == '__main__':
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