Training U-NET on Original Dataset: A Step-by-Step Tutorial

In this tutorial, we will walk you through the process of training U-NET on an original dataset. We will cover the basics of U-NET architecture and dive into the details of dataset preparation, including data augmentation techniques. You will learn how to implement U-NET from scratch, as well as how to fine-tune an existing pre-trained model. We will also share some tips and tricks for optimizing model performance and improving segmentation accuracy. By the end of this tutorial, you will have a solid understanding of how to train U-NET on your own dataset and apply it to a variety of real-world image segmentation tasks. Check out the references below for more information on U-NET tutorials that cover related topics.

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[susmita_jana]

Please give me the link of the dataset from where I can download the dataset for my own practice

[srikanthanmuthiagovindaraj]

I am become a member since yesterday, Will I get code and dataset for "Training U-NET on Original Dataset: A Step-by-Step Tutorial"

[akshaybatra]

Will your UNET model work for images of different sizes and with 1 channel?

[sumantbhanot-]

I have subscribed to your channel membership, how can i get access to the codes and training data

[sarthakdas]

What versions of the libraries are you using?

[confusedbandha]

what is Input funtion here that is Input(input_shape) .where did u define Input function.

[ghostimpact-]

i need help.
i can't connect my gpu to tensorflow does anyone know how to do it. please
its really hard running the above with ram it gives graph-execution-error

[mous_wengli]

Is it possible to associate multiple masks with a single image in the context of image processing? Alternatively, should we duplicate the image for each mask since each mask must be linked to a unique image?

[Sonalikohli-st]

share the source code please. Subscribed your channel but did not get anything.

[vivektomar]

def build_unet(input_shape):
inputs = Input(input_shape)
is Input correct or