thera0810 / boxinstseg

A toolbox for box-supervised instance segmentation.

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)

demo.mp4

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

• BoxInst (CVPR2021)
• DiscoBox (ICCV2021)
• BoxLevelset (ECCV2022)
• Box2Mask (to be released)

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	1x	config	32.0	32.2
BoxInst	R-101	8	model	3x	config	33.1	33.0
DiscoBox	R-50	8	model	3x	config	32.2	31.4(wo ms)
DiscoBox	R-101	8	model	3x	config
Box2Mask-T	R-50	8	model	50e	config
Box2Mask-T	R-101	8	model	50e	config

The above models are trained with ms to make a performance comparison.

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.