crnn.pytorch
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Convolutional recurrent network in pytorch
Can the model provide a confidence for the output result?
Bumps [numpy](https://github.com/numpy/numpy) from 1.17.2 to 1.22.0. Release notes Sourced from numpy's releases. v1.22.0 NumPy 1.22.0 Release Notes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread...
用到的训练的数据集是什么呢
Bumps [pillow](https://github.com/python-pillow/Pillow) from 9.0.0 to 9.0.1. Release notes Sourced from pillow's releases. 9.0.1 https://pillow.readthedocs.io/en/stable/releasenotes/9.0.1.html Changes In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [@radarhere, @hugovk] Restrict builtins within...
it look like this projetc does not support python3
convRelu(5) cnn.add_module('pooling{0}'.format(3), nn.MaxPool2d((2, 2), (2, 1), (0, 1))) # 512x2x16 convRelu(6, True) # 512x1x16 发现代码的BN设置与原论文不同, 貌似这样效果确实更好些, 请问这样做的原因是?
Why is the pooling layer in the network different from the 1 * 2 pooling in the original paper?
![image](https://user-images.githubusercontent.com/82756842/125009531-48250000-e097-11eb-92cc-95f5779fbfb6.png)
Could you please explain this?
Traceback (most recent call last): File "train.py", line 199, in cost = trainBatch(crnn, criterion, optimizer) File "train.py", line 186, in trainBatch cost.backward() File "/home/zhangmingzhou1/anaconda3/envs/torch/lib/python3.6/site-packages/torch/tensor.py", line 195, in backward torch.autograd.backward(self, gradient,...