Comments (1)
if __name__ == "__main__":
for epoch in range(params.nepoch):
train_iter = iter(train_loader)
i = 0
while i < len(train_loader):
cost = train(crnn, criterion, optimizer, train_iter)
loss_avg.add(cost)
i += 1
if i % params.displayInterval == 0:
print('[%d/%d][%d/%d] Loss: %f' %
(epoch, params.nepoch, i, len(train_loader), loss_avg.val()))
loss_avg.reset()
if i % params.valInterval == 0:
val(crnn, criterion)
# do checkpointing
if i % params.saveInterval == 0:
torch.save(crnn.state_dict(), '{0}/netCRNN_{1}_{2}.pth'.format(params.expr_dir, epoch, i))
if you have 100 images and you batch_size if 8, so you will have i from 1 to 100//8+1=13. So, if you set saveInterval bigger than 13, it will never equal to 0.
P.S. It can't recognize vertically oriented text like that.
from crnn-pytorch.
Related Issues (20)
- KeyError : ' ' HOT 1
- Problem loading checkpointed model
- inference accuracy HOT 10
- Output indicates "PAD" char for all columns HOT 3
- A question about pre-trained model HOT 3
- Problem about ctc_loss variable input_length while training HOT 1
- Mean vals and norm vals
- No predictions when training or testing the net !!!
- create image Tensor HOT 2
- Traanning Question HOT 3
- number images train
- Training Problems HOT 2
- 梯度爆炸,loss显示持续显示为inf HOT 1
- img.sub_(0.5).div_(0.5)
- 运行demo用cenn.pth预训练模型显示Expected 512, got 64
- val loss:nan, accuray:0 HOT 1
- [Friendly reminder] About the accuracy of demo.py
- val gpu slow HOT 1
- size mismatch for rnn.1.embedding.weight
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from crnn-pytorch.