PaddleSeg is an easy-to-use image segmentation library designed for a wide range of practical tasks, including semantic, interactive, panoptic, and matting segmentation, as well as 3D segmentation. It offers a rich model zoo with pre-trained models, targeting researchers and developers needing efficient and flexible image segmentation solutions.

How It Works

PaddleSeg is built on the PaddlePaddle deep learning framework, leveraging its dynamic graph execution for flexibility and performance. It provides a unified API for various segmentation tasks, abstracting away complex model implementations. The library supports a modular design, allowing users to easily swap components, customize models, and integrate new research.

Quick Start & Requirements

• Install via pip: pip install paddleseg
• Requires Python 3.7+ and PaddlePaddle (CPU or GPU version).
• Official documentation and tutorials are available at https://github.com/PaddlePaddle/PaddleSeg.

Highlighted Details

• Comprehensive support for multiple segmentation tasks (semantic, interactive, panoptic, matting, 3D).
• Extensive pre-trained model zoo for quick deployment and benchmarking.
• High performance with optimized implementations on PaddlePaddle.
• Supports custom dataset loading and training pipelines.

Maintenance & Community

• Actively maintained by the PaddlePaddle team.
• Community support channels and discussions are available.

Licensing & Compatibility

• Apache 2.0 License.
• Compatible with commercial use and closed-source applications.

Limitations & Caveats

The library primarily targets the PaddlePaddle ecosystem, which may require users to adapt if they are heavily invested in other frameworks like PyTorch or TensorFlow.