JNeRF | JNeRF re-implemented instant

by Jittor C++ Version: 0.1.0 License: Apache-2.0

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

kandi X-RAY | JNeRF Summary

JNeRF is a C++ library. JNeRF has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

JNeRF is an NeRF benchmark based on Jittor. JNeRF supports Instant-NGP capable of training NeRF in 5 seconds and achieves similar performance and speed to the paper.

Support

Quality

Security

License

Reuse

Support

JNeRF has a low active ecosystem.

It has 491 star(s) with 52 fork(s). There are 17 watchers for this library.

It had no major release in the last 12 months.

There are 31 open issues and 9 have been closed. On average issues are closed in 11 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of JNeRF is 0.1.0

Quality

JNeRF has no bugs reported.

Security

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

License

JNeRF 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

JNeRF releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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JNeRF Key Features

No Key Features are available at this moment for JNeRF.

JNeRF Examples and Code Snippets

No Code Snippets are available at this moment for JNeRF.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install JNeRF

JNeRF is a benchmark toolkit and can be updated frequently, so installing in editable mode is recommended. Thus any modifications made to JNeRF will take effect without reinstallation. If you have any installation problems for Jittor, please refer to Jittor. After installation, you can import jnerf in python interpreter to check if it is successful or not.
System: Linux(e.g. Ubuntu/CentOS/Arch), macOS, or Windows Subsystem of Linux (WSL)
Python version >= 3.7
CPU compiler (require at least one of the following) g++ (>=5.4.0) clang (>=8.0)
GPU compiler (optional) nvcc (>=10.0 for g++ or >=10.2 for clang)
GPU library: cudnn-dev (recommend tar file installation, reference link)
GPU supporting: sm arch >= sm_61 (GTX 10x0 / TITAN Xp and above) to use fp16: sm arch >= sm_70 (TITAN V / V100 and above). JNeRF will automatically use original fp32 if the requirements are not meet. to use FullyFusedMLP: sm arch >= sm_75 (RTX 20x0 and above). JNeRF will automatically use original MLPs if the requirements are not meet.

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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