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Seeking ML Model Recommendations for Enhancing OCR on Corrupted Text Images

I am working on a project where I need to perform Optical Character Recognition (OCR) on text-based images. However, these images are corrupted in various ways (e.g., blurred, distorted, low ...
Nurbek Ss's user avatar
1 vote
1 answer
21 views

gnet loss is increasing, while my dnet loss is decreasing, what is wrong with the GAN?

I am developing an MIT open source GAN to generate synthetic structured health data, in the standard FHIR format. I have a running GAN, and it is using 200,000 Synthea Patient FHIR resources to train....
FHIRFLY's user avatar
  • 21
0 votes
0 answers
66 views

WGAN with simplest data

I want to train WGAN (pyTorch) to generate this simple data. Here below my generator and critic architechtures: ...
simpler's user avatar
0 votes
1 answer
233 views

Get data from intermediate layers in a Pytorch model

I was trying to implement SRGAN in PyTorch and I have to write a Content loss function that required me to fetch activations from intermediate layers for both the Generated Image & Original Image. ...
LostAtlas's user avatar
0 votes
1 answer
4k views

How to Connect Convolutional layer to Fully Connected layer in Pytorch while Implementing SRGAN

I was implementing the SRGAN in PyTorch but while implementing the discriminator I was confused about how to add a fully connected layer of 1024 units after the final convolutional layer My input ...
LostAtlas's user avatar
1 vote
0 answers
348 views

Understanding image size changes in DCGAN

I have been studying and trying to implement Generative Adversarial Networks using PyTorch. More precisely I tried to replicate the DCGAN PyTorch Tutorial tutorial using some custom dataset. My code ...
Moonstone5629's user avatar
1 vote
0 answers
88 views

Is it possible to use Inception Model in GANs (DCGAN) using PyTorch(or any other library)?

MAIN ISSUE: Is it possible to use Inception Model (e.g. v3) for DCGAN using PyTorch(any other library)? I've tried to find info how it could be implemented but nothing has been found. It was explained ...
CapJS's user avatar
  • 135
5 votes
1 answer
815 views

How can my Pytorch based GAN output pure B&W with no grayscale?

My goal is to create simple geometric line drawings in pure black and white. I do not need gray tones. Something like this (example of training image): But using that GAN it produces gray tone images....
Todd Chaffee's user avatar
1 vote
0 answers
175 views

Using a DCGAN to create an intrusion detection system

The TL;DR of my question is how do you write a discriminator and generator of a DCGAN in pytorch to accept a csv file instead of an image? I am attempting to partial recreate an experiment from the ...
Buraeen's user avatar
  • 11
1 vote
1 answer
733 views

What is a latent space vector?

I do not understand this about GANs. Apparently the Generator is supposed to receive a latent space vector as its input. Yet I couldn't find an example of how I can implement it in Pytorch. This is a ...
NakedCat's user avatar
  • 113
3 votes
1 answer
217 views

How to optimize the lambdas of a hybrid loss in a deep learning model

I am using a generative adversarial deep learning model (GAN) with a hybrid loss represented by a linear combination of four losses with three $\lambda$'s, something like: $total\_loss = loss_1 + \...
innuendo's user avatar
6 votes
2 answers
7k views

GAN - am I seeing mode collapse? Common fixes not working

I have a 2 part question. Context I am learning about GANs and writing my own starting from the very simplest example of adversarial learning (1-parameter node), then implementing a very simple 1-...
MYO Algorithmic Art's user avatar
2 votes
1 answer
1k views

Perform several different torchvision.transforms on ImageFolder object

I am using pytorch to build DCGAN which i aim to train on custom dataset. I have already posted a question on training DCGAN on small dataset, and of course answer was data augmentation. But i have ...
Stefan Radonjic's user avatar
6 votes
0 answers
614 views

Adversarial Learning for Semantic Segmentation

I am incorporating Adversarial Training for Semantic Segmentation from Adversarial Learning for Semi-Supervised Semantic Segmentation. The idea is like this: The discriminator takes as input a ...
ethelion's user avatar