segmentation_models.pytorch open source analysis

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

Project overview

⭐ 11068 · Python · Last activity on GitHub: 2025-10-29

GitHub: https://github.com/qubvel-org/segmentation_models.pytorch

Why it matters for engineering teams

Segmentation_models.pytorch addresses the practical challenge of implementing reliable semantic segmentation in computer vision projects by providing a wide range of pretrained convolutional and transformer-based backbones. This open source tool for engineering teams simplifies the integration of state-of-the-art models, reducing development time and improving accuracy in image segmentation tasks. It is particularly suited for machine learning and AI engineering teams working on production ready solutions in fields like autonomous vehicles, medical imaging, and satellite image analysis. The project is mature and well-maintained, with a strong user base and extensive pretrained weights, making it dependable for production use. However, it may not be the best choice when lightweight or highly custom models are required, or when teams need a solution optimised for very specific hardware constraints or minimal dependencies.

When to use this project

Use segmentation_models.pytorch when your team needs a robust, well-supported library with a variety of pretrained models for semantic segmentation tasks. Consider alternatives if your project demands ultra-lightweight models or highly custom architectures that fall outside the scope of this repository.

Team fit and typical use cases

Machine learning engineers and AI specialists benefit most from this self hosted option for semantic segmentation, leveraging it to accelerate model development and deployment. It is commonly used in production environments for applications such as medical diagnostics, autonomous navigation, and environmental monitoring, where accurate image segmentation is critical. Data scientists also use it for prototyping and benchmarking segmentation models within real-world product pipelines.

Best suited for

Topics and ecosystem

computer-vision deeplab-v3-plus deeplabv3 dpt fpn image-processing image-segmentation imagenet models pretrained-weights pspnet pytorch segformer segmentation segmentation-models semantic-segmentation transformers unet unet-pytorch unetplusplus

Activity and freshness

Latest commit on GitHub: 2025-10-29. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.