MvSMPLfitting | A multi-view SMPL fitting based on smplify-x
kandi X-RAY | MvSMPLfitting Summary
kandi X-RAY | MvSMPLfitting Summary
MvSMPLfitting is a Python library. MvSMPLfitting has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. However MvSMPLfitting has 11 bugs. You can download it from GitHub.
A multi-view SMPL fitting based on smplify-x.
A multi-view SMPL fitting based on smplify-x.
Support
Quality
Security
License
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Support
MvSMPLfitting has a low active ecosystem.
It has 63 star(s) with 6 fork(s). There are 5 watchers for this library.
It had no major release in the last 6 months.
There are 4 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 MvSMPLfitting is current.
Quality
MvSMPLfitting has 11 bugs (11 blocker, 0 critical, 0 major, 0 minor) and 135 code smells.
Security
MvSMPLfitting has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
MvSMPLfitting code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
MvSMPLfitting 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
MvSMPLfitting 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.
It has 3898 lines of code, 148 functions and 30 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed MvSMPLfitting and discovered the below as its top functions. This is intended to give you an instant insight into MvSMPLfitting implemented functionality, and help decide if they suit your requirements.
- Save the results of a model
- Project a mesh to a given image
- Visualize the results of an image
- Calls keyboard
- Nonlinear solver
- Convert a matrix to an AA matrix
- Decodes the input tensor into a matrix
- Convert a rotation matrix to an angle
- Load a Vposer
- Forward the camera to the given points
- Fix the parameters
- Calculate the mean and standard deviation
- Handle points move
- Parse config file
- Load weights as numpy arrays
- Handle click event
- Estimate the translation for the given image
- Sample from the latent space prior distribution
- Compute the log likelihood for a given pose
- Compute a 3D rotation matrix
- Generate a forward transform
- Compute the model for each view
- Compute the loss of a scene
- Compute the forward projection
- Render a multiperson layer
- Visualize fitting
Get all kandi verified functions for this library.
MvSMPLfitting Key Features
No Key Features are available at this moment for MvSMPLfitting.
MvSMPLfitting Examples and Code Snippets
No Code Snippets are available at this moment for MvSMPLfitting.
Community Discussions
No Community Discussions are available at this moment for MvSMPLfitting.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install MvSMPLfitting
You can download it from GitHub.
You can use MvSMPLfitting 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.
You can use MvSMPLfitting 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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