keras/basnet_duts

Model Overview

Model Summary

Deep semantic segmentation algorithms have improved a lot recently, but still fails to correctly predict pixels around object boundaries.We implement Boundary-Aware Segmentation Network (BASNet), using two stage predict and refine architecture, and a hybrid loss it can predict highly accurate boundaries and fine structures for image segmentation. This model is supported in both KerasCV and KerasHub. KerasCV will no longer be actively developed, so please try to use KerasHub. Weights are released under the MIT License . Keras model code is released under the Apache 2 License.

Links

• BASNet Quickstart Notebook
• [BASNet API Documentation](coming soon)
• BASNet Model Card
• KerasHub Beginner Guide
• KerasHub Model Publishing Guide

Installation

Keras and KerasHub can be installed with:

pip install -U -q keras-hub
pip install -U -q keras

Jax, TensorFlow, and Torch come preinstalled in Kaggle Notebooks. For instructions on installing them in another environment see the Keras Getting Started page.

Presets

The following model checkpoints are provided by the Keras team. Full code examples for each are available below.

Preset name	Parameters	Description
basnet_duts	108.89M	BASNet model with a 34-layer ResNet backbone, pre-trained on the DUTS image dataset at a 288x288 resolution.