Deep-Detail-Enhancement-for-Any-Garment | repository contains the implementation of Deep Detail

by MengZephyr Python Version: Current License: No License

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

kandi X-RAY | Deep-Detail-Enhancement-for-Any-Garment Summary

Deep-Detail-Enhancement-for-Any-Garment is a Python library. Deep-Detail-Enhancement-for-Any-Garment has no bugs, it has no vulnerabilities and it has low support. However Deep-Detail-Enhancement-for-Any-Garment build file is not available. You can download it from GitHub.

This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in Eurographics 2021.

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Deep-Detail-Enhancement-for-Any-Garment has a low active ecosystem.

It has 46 star(s) with 6 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Deep-Detail-Enhancement-for-Any-Garment is current.

Quality

Deep-Detail-Enhancement-for-Any-Garment has no bugs reported.

Security

Deep-Detail-Enhancement-for-Any-Garment has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Deep-Detail-Enhancement-for-Any-Garment does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

Deep-Detail-Enhancement-for-Any-Garment releases are not available. You will need to build from source code and install.

Deep-Detail-Enhancement-for-Any-Garment has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

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

Crop random image
Random image
Calculate the bounding box of a patch
Do geo optimization on a given vertex
Reads vertical CC flag
Computes the smoothed loss
Get a list of images from a list of BatchIDs
Plot a gram feature embedding
Evaluate the QR code
Forward computation
Calculate content activations
Compute the loss of the given noise
Generate cropGropG
Get data from a list of files
Generate a random BBox patch
Calculate the overlap variance of the mesh
Forward the transformation
Reads an OOBJ file
Calculate LAPNorms for the given vertices
Train model
This function takes a list of input files and returns a list of matrices
Saves a PLY file
Write a PLY file
Calculate the features of the image
Runs test
This function generates the vertices of the vertices of the vertices
Read an OOBJ file
Generates a list of AADATA objects

Get all kandi verified functions for this library.

Deep-Detail-Enhancement-for-Any-Garment Key Features

No Key Features are available at this moment for Deep-Detail-Enhancement-for-Any-Garment.

Deep-Detail-Enhancement-for-Any-Garment Examples and Code Snippets

No Code Snippets are available at this moment for Deep-Detail-Enhancement-for-Any-Garment.

Community Discussions

No Community Discussions are available at this moment for Deep-Detail-Enhancement-for-Any-Garment.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install Deep-Detail-Enhancement-for-Any-Garment

You can download it from GitHub.
You can use Deep-Detail-Enhancement-for-Any-Garment 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.

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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