songw-zju / BoxInstSeg

A toolbox for box-supervised instance segmentation.

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Introduction

BoxInstSeg is a toolbox that aims to provide state-of-the-art box-supervised instance segmentation algorithms. It is built on top of mmdetection. The main branch works with Pytorch 1.6+ or higher (we recommend Pytorch 1.9.0)

Major features

  • Support of instance segmentation with only box annotations

    We implement multiple box-supervised instance segmentation methods in this toolbox,(e.g. BoxInst, DiscoBox). This toolbox can achieve the similar performance as the original paper.

  • MMdetection feature inheritance

    This toolbox doesn't change the structure and logic of mmdetection. It inherits all features from MMdetection.

Model Zoo

Supported methods

COCO (val)

method Backbone GPUs Models sched. config AP (this rep) AP(original rep/paper)
BoxInst R-50 8 model 1x config 30.7 30.7
BoxInst R-50 8 model 3x config 32.1 31.8
BoxInst R-101 8 model 3x config 32.0 32.2
DiscoBox R-50 8 model 3x config 31.7
DiscoBox R-101 8 model 3x config 33.1

Pascal VOC

method Backbone Models sched. config AP
BoxInst R-50 model 3x config

Multiple pretrained models based on the Pascal VOC and COCO and more datasets are coming as soon as possible.

Installation and Getting Started

This is built on the MMdetection (V2.25.0). Please refer to Installation and Getting Started for the details of installation and basic usage. We also recommend the user to refer the office introduction of MMdetection.

License

This project is released under the Apache 2.0 license.

Acknowledgement

This project is built based on MMdetection and part of module is borrowed from the original rep of Adelaidet and DiscoBox.

More

  • This repo will update the survey of box-supervised instance segmentation, we highly welcome the user to develop more algorithms in this toolbox.

  • If this rep is helpful for your work, please give me a star.

About

A toolbox for box-supervised instance segmentation.

License:Apache License 2.0


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