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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

https://user-images.githubusercontent.com/32033843/207869884-5254b2ba-5e3d-44fb-bbd6-b26d07c9b404.mp4

Update

Model Zoo

<summary> Supported methods </summary>

COCO (val)

methodBackboneGPUsModelssched.configAP (this rep)AP(original rep/paper)
BoxInstR-508model1xconfig30.730.7
BoxInstR-508model3xconfig32.131.8
BoxInstR-1018model1xconfig32.032.2
BoxInstR-1018model3xconfig33.133.0
DiscoBoxR-508model3xconfig32.231.4(wo ms)
DiscoBoxR-1018model3xconfig33.4--
Box2Mask-TR-508model50econfig35.936.1
Box2Mask-TR-1018model50econfig38.237.9
Box2Mask-TSwin-L8model50econfig41.9/42.541.3/42.4

Pascal VOC

methodBackboneGPUsModelssched.configAPAP_50AP_75
BoxInstR-504model3xconfig32.060.230.2
BoxInstR-1014model3xconfig34.262.433.2
DiscoBoxR-504model3xconfig32.961.031.5
DiscoBoxR-1014model3xconfig34.663.033.0
Box2Mask-TR-504model50econfig41.468.942.1
Box2Mask-TR-1014model50econfig43.270.844.4

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.

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