U-Net architecture

Submitted by Competitive-Good4690 t3_ymgg7o in deeplearning

Hello guys,

I’m a graduate student working on kidney image segmentation using UNet architecture.. can you guide me through (the codes) I’m trying to implement it using tensorflow2.0 (image size =28,256,192) MRI image (.nrrd file) I’m unable to find any U-Net (non model.fit) code.. so I’m trying to use Class U_Net(tf.keras.Model): Def U_Net(Img_size) … And so on I feel like I’m on the wrong track.

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sgjoesg t1_iv42h3k wrote

You can see abhishek thakur's video on the implementation of unet architecture. He explains it very well step by step. edit: i didnt see you wanted tf2.0. If i get some resources, will fwd it to you.

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sgjoesg t1_iv42snj wrote

Also, what do you mean by non model.fit? And why?

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Competitive-Good4690 OP t1_iv4e66u wrote

So model.fit is an inbuilt function for training the model which I don’t want to use. I want to define the model on my own

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sgjoesg t1_iv4ezuu wrote

As far as i know, if you create your own class inheriting from tf.keras, then that class can use .fit function. Eg class unet(tf.keras) Model_definition_as_per_arch model = unet() model.fit(data)

So you have the control to use your own model, and use keras's easy training loop as well.

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Competitive-Good4690 OP t1_iv4fdo1 wrote

Yes thank you I’m Referring to Connor Shorten’s video on U-Net (Keras) he’s saying exactly what u just said.. thank you for the response.. really appreciated.. Abhisek Thakur is using PyTorch but he did explain the concept well

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sgjoesg t1_iv4hum4 wrote

Glad i could help(in some way lol)💯

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