sem_seg | customizable SOTA Semantic Segmentation models
kandi X-RAY | sem_seg Summary
kandi X-RAY | sem_seg Summary
sem_seg is a Python library. sem_seg 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.
Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch. Refer to MODELS for benchmarks and available pre-trained models. And check BACKBONES for supported backbones. Notes: Most of the methods do not have pre-trained models. It's very difficult to combine different models with pre-trained weights in one repository and limited resource to re-train myself. Refer to DATASETS for more details and dataset preparation.
Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch. Refer to MODELS for benchmarks and available pre-trained models. And check BACKBONES for supported backbones. Notes: Most of the methods do not have pre-trained models. It's very difficult to combine different models with pre-trained weights in one repository and limited resource to re-train myself. Refer to DATASETS for more details and dataset preparation.
Support
Quality
Security
License
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Support
sem_seg has a low active ecosystem.
It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
sem_seg has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of sem_seg is current.
Quality
sem_seg has no bugs reported.
Security
sem_seg has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
sem_seg is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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sem_seg 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.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of sem_seg
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of sem_seg
sem_seg Key Features
No Key Features are available at this moment for sem_seg.
sem_seg Examples and Code Snippets
No Code Snippets are available at this moment for sem_seg.
Community Discussions
No Community Discussions are available at this moment for sem_seg.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install sem_seg
You can download it from GitHub.
You can use sem_seg 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 sem_seg 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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