sgan | Social GAN : Socially Acceptable Trajectories | Machine Learning library

by agrimgupta92 Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | sgan Summary

sgan is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. sgan has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018

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Support

sgan has a low active ecosystem.

It has 735 star(s) with 250 fork(s). There are 18 watchers for this library.

It had no major release in the last 6 months.

There are 57 open issues and 50 have been closed. On average issues are closed in 21 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of sgan is current.

Quality

sgan has 0 bugs and 0 code smells.

Security

sgan has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

sgan code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

sgan is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

sgan releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed sgan and discovered the below as its top functions. This is intended to give you an instant insight into sgan implemented functionality, and help decide if they suit your requirements.

Calculate the accuracy of the loss function
R Computes the displacement error between two trajectories
Calculate the Fde de - displacement error
Calculate displacement error
Perform forward computation
Repeat a tensor
Calculate grid coordinates
Calculate the bounding box of the given position
Performs a single generator step
Forward forward computation
Add noise to the input tensor
Check if the mlp decoder needs
Get noise
Perform discriminator step
R Evaluate the displacement model
Calculate the sum of squared error
Forward computation
Create a TrajectoryGenerator from a checkpoint
Return data loader
Calculates the GAN divergence between two sets of scores
Compute the loss between the input and target
Calculate the total norm of a list of parameters
Calculates GAN loss
Determine the dtypes to use
Returns the path to the dataset

Get all kandi verified functions for this library.

sgan Key Features

No Key Features are available at this moment for sgan.

sgan Examples and Code Snippets

No Code Snippets are available at this moment for sgan.

Community Discussions

Trending Discussions on sgan

How to implement fractionally strided convolution layers in pytorch?

Replicate Creating Dynamic Controls on Create/ EDIT Pages

I keep getting an Assertion Error with StyleGAN

QUESTION

How to implement fractionally strided convolution layers in pytorch?

Asked 2021-Feb-20 at 10:51

Before everything, I searched google and StackOverflow but I do not find any similar questions so here I propose a new one.

I'm interested in this paper and want to implement this SGAN for my project. The paper mentioned that its generator network is composed of "a stack of fractionally strided convolution layers", I found two different ways of implementing this in pytorch, one is:

...

ANSWER

Answered 2021-Feb-20 at 10:51

tldr; There are some shape constraints but both perform the same operations.

The output shape of nn.ConvTranspose2d is given by y = (x − 1)s - 2p + d(k-1) + p_out + 1, where x and y are the input and ouput shape, respectively, k is the kernel size, s the stride, d the dilation, p and p_out the padding and padding out. Here we keep things simple with s=1, p=0, p_out=0, d=1.

Therefore, the output shape of the transposed convolution is:

Source https://stackoverflow.com/questions/66287552

QUESTION

Replicate Creating Dynamic Controls on Create/ EDIT Pages

Asked 2020-Sep-05 at 14:19

I want to display a List of File Attachments (filename only), the ability to Add new Attachments on the CREATE page works perfectly fine. I use the code from here See Screenshot below..

...

ANSWER

Answered 2020-Sep-05 at 14:19

In your current jquery code new row was appending inside controls first div i.e : div:first because as you look at your html structure i.e :

Source https://stackoverflow.com/questions/63745890

QUESTION

I keep getting an Assertion Error with StyleGAN

Asked 2020-Jan-08 at 22:27

Recently I have been playing around with StyleGAN and I have generated a dataset but I get the following when I try to run train.py.

...

ANSWER

Answered 2020-Jan-08 at 21:50

As answered by @Chrispresso in the comments of this question, the directory that I was referencing in the following line was invalid and had to set it to a valid directory.

Source https://stackoverflow.com/questions/59654172

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install sgan

All code was developed and tested on Ubuntu 16.04 with Python 3.5 and PyTorch 0.4.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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