generative | A repository of generative artworks created with R | Animation library

I am developing a VAE using this: dataset

I have used keras tutorial code and I have developed my own encoder and decoder, the problem is that when I run vae.fit() I get 'int' object is not subscriptable. What am I doing wrong?

I am training a VQVAE with this dataset (64x64x3). I have downloaded it locally and loaded it with keras in Jupyter notebook. The problem is that when I ran fit() to train the model I get this error: ValueError: Layer "vq_vae" expects 1 input(s), but it received 2 input tensors. Inputs received: [, ] . I have taken most of the code from here and adapted it myself. But for some reason I can't make it work for other datasets. You can ignore most of the code here and check it in the page, help is much appreciated.

The code I have so far:

I have seen multiple uses of both tf.keras.layers.Flatten() (ex. here) and tf.keras.layers.Input() (ex. here). After reading the documentation, it is not clear to me

1. whether either of them uses the other
2. whether both can be used interchangeably when introducing to a model an input layer (let's say with dimensions (64, 64))

Here i'am asking again on Stack Overflow :), when i try to make a GoogleMapsController variable it show this

I was tasked with the creation of a dataset to test the functionality of the code we're working on.

The dataset must have a group of tensors that will be used later on in a generative model.

I'm trying to save the tensors to a .pt file, but I'm overwriting the tensors thus creating a file with only one. I've read about torch.utils.data.dataset but I'm not able to figure out by my own how to use it.

Here is my code:

Hello I am starting in the world of neural networks, I have taken as a total basis the example of the book "Python Deep Learning" from the publisher Marcombo, in this a Generative Adversarial Networks is generated based on an example of the book, the following was developed code

I'm following a tutorial by George Francis in the tutorial after some initial examples he shows how to use image data to create random layouts.

I'm trying to work out how to get the image data from a canvas created using paper.js, as I need to get the rgb values from each individual pixel on the canvas

Link to codepen

Unknowns:

• Do I need to use the rasterize() method on the shape I've created?

Currently I am attempting the following:

I am trying to write a tiny recursive rewrite system inspired by Aristid Lindenmayers L-System basically to learn Prolog as well as to think about generative concepts in Prolog. I would like to achieve this without DCG. Due to the initial generate. and output predicate with side effects it is not a 100% pure prolog idea. Don´t hesitate to take the concept apart.

My main problem is at the end of the listing. Matching the rule for every element in the original list and creating a new list with the result of each substitution.

[a] the Axiom becomes [a,b] becomes [a,b,a] and so on. Or better as a list of lists [[a,b],[a]] to keep it more flexible and comprehensible and then flatten it later?

Basic example without constants, which could be added in a similar way. The Axiom is just used one time at the start. The idea is to encode the rule name or symbol to exchange and the symbols it should be exchanged with, as a fact/relation. Start with generate. would repeat it 20 times with a counter.

Source Code: https://editor.p5js.org/theruantan/sketches/aFXKo_s86

Basically I'm trying to do a pseudo generative poster that swaps between 3 artworks that I have predesigned. The idea is to make load one artpiece, wait a few seconds then reverse (essentially wipe it away) the drawing to a blank canvas then load the next and repeat endlessly.

I'm just trying to recreate the reversal animation that I saw here: https://www.reddit.com/r/generative/comments/q6krwj/lines_p5js/