GAN | Generate images via a Generative Adversarial Network | Machine Learning library

I am trying to do some sample code of GAN, here comes the generator.

I want to see the visualized model but, this is not the model.

Model.summary() is not the function of tensorflow but it is keras?? if so how can I see visualized model??

I have a GAN that returns a predicted torch.tensor. To guide this network, I have a loss function which is a summation of binary cross entropy loss (BCELoss) and Wasserstein distance. However, in order to calculate Wasserstein distance, I am using scipy.stats.wasserstein_distance function from SciPy library. As you might know, this function requires two NumPy arrays as input. So, to use this function, I am converting my predicted tensor and ground-truth tensor to NumPy arrays as follows

I am trying to implement a simple GAN in google collaboratory, After using transforms to normalize the images, I want to view it at the output end to display fake image generated by the generator and real image side by in the dataset once every batch iteration like a video.

I'm working on training a GAN through Google Colab with a dataset of photos I scraped from Wikiart and converted to 1024x1024, but keep getting this error when creating the tfrecords:

so I'd like to simulate CT images from ultrasound images using GAN and I am currently working on the data preparation.

By nature of the ultrasound these images are stored in a cone shaped kind of form:

But what I want to have is the image in the following form:

I belief it is easier to simulate the CT image that way.

I am using simple ITK. I guess this should be a common transformation. Is there maybe a filter from sITK that I am not aware of? Or is there an other simple way to do this transformation?

I am using this API - https://rapidapi.com/rapidapi/api/movie-database-imdb-alternative I am using the JavaScript implementation and I can't see the values I am supposed to. This is not my first work with APIs, but I don't understand this behavior.

My code:

I'm trying to parse this flag 'dataroot' (string type).

Consider this as a demo code:

I'm trying to build a basic GAN to familiarise myself with Pytorch. I have some (limited) experience with Keras, but since I'm bound to do a larger project in Pytorch, I wanted to explore first using 'basic' networks.

I'm using Pytorch Lightning. I think I've added all necessary components. I tried passing some noise through the generator and the discriminator separately, and I think the output has the expected shape. Nonetheless, I get a runtime error when I try to train the GAN (full traceback below):

RuntimeError: mat1 and mat2 shapes cannot be multiplied (7x9 and 25x1)

I noticed that 7 is the size of the batch (by printing out the batch dimensions), even though I specified batch_size to be 64. Other than that, quite honestly, I don't know where to begin: the error traceback doesn't help me.

Chances are, I made multiple mistakes. However, I'm hoping some of you will be able to spot the current error from the code, since the multiplication error seems to point towards a dimensionality problem somewhere. Here's the code.

I tried to train gan on some monkey pics but it crashes colab for unknown reason if try to train it. I am using 1370 128*128 monkey images.

I have no idea where the issue might be, please respond

btw the runtime is gpu, so the problem doesn't linked to that