CLIP-Mesh | Official implementation of CLIP-Mesh : Generating

by NasirKhalid24 Python Version: Current License: MIT

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

kandi X-RAY | CLIP-Mesh Summary

CLIP-Mesh is a Python library. CLIP-Mesh 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.

Official implementation of CLIP-Mesh: Generating textured meshes from text using pretrained image-text models

Support

Quality

Security

License

Reuse

Support

CLIP-Mesh has a low active ecosystem.

It has 343 star(s) with 33 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 6 have been closed. On average issues are closed in 10 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of CLIP-Mesh is current.

Quality

CLIP-Mesh has no bugs reported.

Security

CLIP-Mesh has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

CLIP-Mesh 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

CLIP-Mesh 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.

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CLIP-Mesh Key Features

No Key Features are available at this moment for CLIP-Mesh.

CLIP-Mesh Examples and Code Snippets

No Code Snippets are available at this moment for CLIP-Mesh.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install CLIP-Mesh

(Work in Progress!) - The following Google Collab notebooks are the best way to get started:.
Clone this repository recursively to get all submodules - use submodule update to get downstream submodules. Setup Conda environment and install packages. Install loop subdivison code and DALLE-2 (not that DALLE-2 is from an earlier commit so existing install may not work).

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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