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How to use the pyrnn.gz models created in ocropy for prediction in clstm, as clstm prediction seems faster than the ocropy's prediction?
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Thank you very much for your work. I've combined ResNet with Kan, using ResNet for feature extraction and replacing the linear layer with KAN for classification. Along the way, I've noticed some chara…
CYYJL updated
1 month ago
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### Code version (Git Hash) and PyTorch version
### Dataset used
I used NTU‘s RGB-D dataset same as you, but I used ColorX and ColorY information, not 3 channels that you used.
### Expected beh…
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NBN denotes no batch normalization.
In the original paper. In table 1. The author use conv2d 1x1, NBN in the 1x1x960 to 1x1x1280, which means they don't use batch norm in fc layers, but your code use…
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Hello, so I've been trying to use Coxtime from your package to do churn analysis, but I'm getting some problems on the output, namely I'm getting the same output, in this case the same survival curve,…
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Hello, thanks for the great code!
Is there a reason for treating all images independently and not making batches for training?
Cheers
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I have fine-tuned an SSD-Mobilenetv2 with train config fixed resize 300x300 built using tensorflow objection detection API and saved in TF Saved_Model format.
Questions:
- How during inference it i…
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hello,
i've managed to execute the visualize sense layer example,
but I have not manged to reproduce results using other graphs (like the current [tensorflow classification tutorial graph](https:/…
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The implementation of adding losses in the repo is so strange. Does anyone explain some a bit of the following code, and help me with how to add a custom metrics in it?
```
# Add Losses
# F…
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I would like to convert sentence bert model from pytorch to tensorflow use onnx, and tried to follow the standard onnx procedure for converting a pytorch model. But I'm having difficulty determining t…