Comments (5)
Sounds about the same that I get with the latest version of the code. As mentioned in the first comment, I used to get an error of 6-7 degrees before commit 2a4fe4b. I suspect that the old rotate
method introduced some artefacts that made it easier for the network to figure out the angle. I'm not planning to investigate the issue further but if you find the reason please let me know :)
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@d4nst
Hi,
I got the accuracy 29-30 degrees after 50 epoch. It is right?
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@d4nst Hi. It's off topic, but can You explain why you are using Sigmoid activation in output Dense layer in regression task? I've always thought that regression uses no activations on output.
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Yes, you are right. It is not recommended to use sigmoid as an output when training with L1/L2 loss. I believe that I tried to train the model without the sigmoid and the result was very similar though.
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My tensorflow stops without erros at epoch 6.
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Related Issues (20)
- input array from shape error HOT 2
- Model Retraining- Transfer Learning HOT 3
- Image size for training and testing
- rough estimation of angle and accuracy with certain angle error HOT 3
- requirements.txt HOT 1
- the street model size is too big use thr ResNet
- Error message when training model HOT 3
- Can we use this code to train for our custom data HOT 7
- Need more information? HOT 7
- ValueError: Unknown layer: Merge HOT 6
- terminate called without an active exception HOT 1
- Can rotnet trian on vgg instead of resnet 50? HOT 1
- Is U-Net architecture a suitable contender for your model?
- How to train my own data set
- How to train with GPU HOT 2
- Maybe the network didn't learn the horizontal information HOT 4
- val_angle_error is too high
- Implementation of `train_street_view` over PyTorch HOT 1
- Train with smaller classes HOT 7
- Not able usee
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