BalaGAN | art image-to-image translation methods | Machine Learning library
kandi X-RAY | BalaGAN Summary
kandi X-RAY | BalaGAN Summary
State-of-the-art image-to-image translation methods tend to struggle in an imbalanced domain setting, where one image domain lacks richness and diversity. We introduce a new unsupervised translation network, BalaGAN, specifically designed to tackle the domain imbalance problem. We leverage the latent modalities of the richer domain to turn the image-to-image translation problem, between two imbalanced domains, into a balanced, multi-class, and conditional translation problem, more resembling the style transfer setting. Specifically, we analyze the source domain and learn a decomposition of it into a set of latent modes or classes, without any supervision. This leaves us with a multitude of balanced cross-domain translation tasks, between all pairs of classes, including the target domain. During inference, the trained network takes as input a source image, as well as a reference or style image from one of the modes as a condition, and produces an image which resembles the source on the pixel-wise level, but shares the same mode as the reference. We show that employing modalities within the dataset improves the quality of the translated images, and that BalaGAN outperforms strong baselines of both unconditioned and style-transfer-based image-to-image translation methods, in terms of image quality and diversity.
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Top functions reviewed by kandi - BETA
- Forward the model
- Calculate the fake loss
- Calculates the cross entropy loss
- Performs the forward computation
- Create GAN grid
- Compute the style of the model
- Translate a simple text
- Load the state of a given ck
- Train the model
- Forward forward computation
- Calculate the nt_ent_loss criterion
- Write 1 image files
- Forward a single image
- Returns a data loader for training images
- Returns a DataLoader for modalities extraction
- Load encoder from checkpoint directory
- Calculates the gradients of the model
- Calculate the average loss
- Get modalities
- Generate a grid of modality
- Run inference
- Evaluate the model
- Returns a list of loaders
- Translates from source_data to target_data
- Setup GPU configuration
- Start the optimizer
BalaGAN Key Features
BalaGAN Examples and Code Snippets
Community Discussions
Trending Discussions on BalaGAN
QUESTION
I have been struggling to do this (every DAY!) for at least a month. I have searched stackoverflow, I have read MDN array, string, regex, etc., references over and over and over again, and nothing has helped. I am somewhat familiar with regex, but this is over my head. I trust that somebody here will solve this with one line of code, which is why I waited until I'm about to throw my computer out the window before asking for help. I really wanted to find the solution for myself, but I simply cannot do it.
I was enjoying a game of cryptograms, where random letters are used to sort of 'encode' a poem or story, I probably don't need to describe it here, but here's a picture just in case.
So I thought it would be a good exercise to create a form where you can enter a pattern made up of a combination of letters, numbers, and "?" for unknown. In the image, you see the word represented with "YACAZ", there are two A's in that word, so you know those two letters are the same. So in my function, you would use any number 0 - 9 as placeholders, so using the same example, you would enter "?1a1?".
Here's what I have at the moment. Every time I try to iterate through the arrays that regex gives me, I end up at the same place, trying - and failing - to compare two sets of nested arrays with each other. No matter how I try to break them down and compare them, it ends up becoming a huge non-functioning mess. I can get the placeholder indexes, but then what?
I have nothing against lodash, but I have very little experience with it, so maybe it could help with this? It doesn't do anything that cannot be done with plain vanilla javascript, does it?
...ANSWER
Answered 2020-Dec-31 at 00:49From the above comment of mine, I'm still not quite sure whether the next provided approach does somehow meet the OP's goal.
But if it is about creating a regex from a custom replacement/substitute pattern and then just filtering a wordlist by this regex (and maybe even capturing the correct characters, one might give the following code a try.
There is a limitation to it though; The digit range for describing the custom placeholder pattern is limited from 1
to 9
(Zero will be excluded) since this matches exactly the definition/limitation of regex capture groups (and how one does access them).
QUESTION
I have a scanned pdf file and I try to extract text from it. I tried to use pypdfocr to make ocr on it but I have error:
"could not found ghostscript in the usual place"
After searching I found this solution Linking Ghostscript to pypdfocr in Windows Platform and I tried to download GhostScript and put it in environment variable but it still has the same error.
How can I searh text in my scanned pdf file using python?
Thanks.
Edit: here is my code sample:
...ANSWER
Answered 2018-Jul-12 at 22:23Take a look at this library: https://pypi.python.org/pypi/pypdfocr but a PDF file can have also images in it. You may be able to analyse the page content streams. Some scanners break up the single scanned page into images, so you won't get the text with ghostscript.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install BalaGAN
You can use BalaGAN like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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