luna

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Hello @JordanMakesMaps, I checked the preprocessing for resnets and it doesn't do anything, so if someone wants to use pretrained imagenet weights he shouldn't scale his images to the range...

I checked the paper "Deep Residual Learning for Image Recognition" I think the images were normalised, they were substracted by the mean. ![image](https://user-images.githubusercontent.com/48836506/122292325-c86ba180-ceed-11eb-9b9e-817383ff7abf.png)

Thank you @JordanMakesMaps for your answer, I don't know why I was confused, you made it clear for me, thank you.

hello @dennywangtenk did adding dropout help you overcome the problem of overfitting ?

Hello, Yes there isn't dropout layers in the implementation of unet, but you can use regularizers set_regularization(model, kernel_regularizer=keras.regularizers.l2(0.001),bias_regularizer=keras.regularizers.l2(0.001)) you can also try data augmentation. But if it is necessary to...

Hi, I'm facing the same problem, please tell me if you resolved it ?

got the same error when I runned docker-compose up