InvGAN | Official codebase of our paper Invert and Defend

by yogeshbalaji Python Version: Current License: Apache-2.0

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

kandi X-RAY | InvGAN Summary

InvGAN is a Python library. InvGAN 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.

Download the pre-trained gans and classifiers from the following links into the root directory:.

Support

Quality

Security

License

Reuse

Support

InvGAN has a low active ecosystem.

It has 10 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

InvGAN has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of InvGAN is current.

Quality

InvGAN has 0 bugs and 0 code smells.

Security

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

InvGAN code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

InvGAN is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

InvGAN 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.

It has 15661 lines of code, 958 functions and 145 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Create a white white box
Parse parameters
Reconstruct a dataset
Train model
Gets the label of the given tensor
Generates the target function
Train the model
Infer the list of available devices
Zips a list of arguments
Calculate the average of gradients
Build a fixed - max attack recipe
Prepare tensorflow for optimization
Bundle examples with the given goal
Performs attack on a single run
Computes the class and probability of each class
Main function for dknn
Basic Max confidence recommendations
Generates an attack
Trains the model
Blackbox
Generate a confidence report
Reconstruct the model
Generate a learning rate model
An SNNL example
Reconstructs the model
Reconstruct a new dataset
Reconstructs the given images
Build a confidence report

Get all kandi verified functions for this library.

InvGAN Key Features

No Key Features are available at this moment for InvGAN.

InvGAN Examples and Code Snippets

No Code Snippets are available at this moment for InvGAN.

Community Discussions

No Community Discussions are available at this moment for InvGAN.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install InvGAN

Download the pre-trained gans and classifiers from the following links into the root directory:.
Install pyenv from https://github.com/pyenv/pyenv#installation
Create a directory for InvGAN:
git clone git@github.com:yogeshbalaji/InvGAN.git invgan
cd invgan Now you should be in the project root directory.
Run the setup script ./setup.sh
Download datasets:

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 .

Find more information at: