Joint-3D-Face-Reconstruction-Network | This is an official python implementation of PRN

by rickyHong Python Version: Current License: MIT

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

kandi X-RAY | Joint-3D-Face-Reconstruction-Network Summary

Joint-3D-Face-Reconstruction-Network is a Python library. Joint-3D-Face-Reconstruction-Network 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.

This is an official python implementation of PRN. The training code will be released(about two months later). PRN is a method to jointly regress dense alignment and 3D face shape in an end-to-end manner. More examples on Multi-PIE and 300VW can be seen in YouTube .

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Support

Joint-3D-Face-Reconstruction-Network has a low active ecosystem.

It has 4 star(s) with 2 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

Joint-3D-Face-Reconstruction-Network has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Joint-3D-Face-Reconstruction-Network is current.

Quality

Joint-3D-Face-Reconstruction-Network has no bugs reported.

Security

Joint-3D-Face-Reconstruction-Network has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Joint-3D-Face-Reconstruction-Network 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

Joint-3D-Face-Reconstruction-Network 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 are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed Joint-3D-Face-Reconstruction-Network and discovered the below as its top functions. This is intended to give you an instant insight into Joint-3D-Face-Reconstruction-Network implemented functionality, and help decide if they suit your requirements.

Performs a texture editing
Get the vertices of a mesh
Render a texture
Get all colors from a texture
Computes the visibility of a triangle
Compute visibility of vertices of vertices
Calculate the depth buffer
Process an image
Predict on an image
Predict from an image
Estimate the pose from vertices
Convert rotation matrix to angle
Convert P matrix to s r t
Map a texture to a texture
Calculate weight of a point
Flatten the vertices of the vertices
Get the Landmarks for a given position
Plot vertices
Write an object to an object
Get the colors from an image
Get the UV mask for the given triangles
Plot kpt points
Draws a box plot
Calculate the depth of a triangle
Write an object with a texture
Generate a depth image

Get all kandi verified functions for this library.

Joint-3D-Face-Reconstruction-Network Key Features

No Key Features are available at this moment for Joint-3D-Face-Reconstruction-Network.

Joint-3D-Face-Reconstruction-Network Examples and Code Snippets

No Code Snippets are available at this moment for Joint-3D-Face-Reconstruction-Network.

Community Discussions

No Community Discussions are available at this moment for Joint-3D-Face-Reconstruction-Network.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install Joint-3D-Face-Reconstruction-Network

You can download it from GitHub.
You can use Joint-3D-Face-Reconstruction-Network 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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