r3det-pytorch | R3Det based on mmdet

by SJTU-Thinklab-Det Python Version: Current License: Apache-2.0

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

kandi X-RAY | r3det-pytorch Summary

r3det-pytorch is a Python library. r3det-pytorch 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.

R3Det based on mmdet 2.19.0

Support

Quality

Security

License

Reuse

Support

r3det-pytorch has a low active ecosystem.

It has 31 star(s) with 4 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 9 have been closed. On average issues are closed in 5 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of r3det-pytorch is current.

Quality

r3det-pytorch has no bugs reported.

Security

r3det-pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

r3det-pytorch 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

r3det-pytorch 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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r3det-pytorch Key Features

No Key Features are available at this moment for r3det-pytorch.

r3det-pytorch Examples and Code Snippets

No Code Snippets are available at this moment for r3det-pytorch.

Community Discussions

No Community Discussions are available at this moment for r3det-pytorch.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install r3det-pytorch

It is best to use opencv-python greater than 4.5.1 because its angle representation has been changed in 4.5.1. The following experiments are all run with 4.5.3.
Please change path in configs to your data path. For DOTA dataset, please crop the original images into 1024×1024 patches with an overlap of 200 by run. Please change path in ss_trainval.json, ss_test.json to your path. (Forked from BboxToolkit, which is faster then DOTA_Devkit.).

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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