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谢昕辰 c448646a92
[Doc] Refine doc and fix links (#2821) 
## Motivation

- Create the `main` branch

## Modification

Modify links from `dev-1.x` to `main`
2023-03-31 16:26:30 +08:00
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configs
CodeCamp #150 [Feature] Add ISNet (#2400)
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CodeCamp #150 [Feature] Add ISNet (#2400)
2023-01-04 20:39:03 +08:00
README.md
[Doc] Refine doc and fix links (#2821)
2023-03-31 16:26:30 +08:00

README.md

ISNet

ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation

Description

This is an implementation of ISNet. Official Repo

Usage

Prerequisites

  • Python 3.7
  • PyTorch 1.6 or higher
  • MIM v0.33 or higher
  • MMSegmentation v1.0.0rc2 or higher

All the commands below rely on the correct configuration of PYTHONPATH, which should point to the project's directory so that Python can locate the module files. In isnet/ root directory, run the following line to add the current directory to PYTHONPATH:

export PYTHONPATH=`pwd`:$PYTHONPATH

Training commands

mim train mmsegmentation configs/isnet_r50-d8_8xb2-160k_cityscapes-512x1024.py --work-dir work_dirs/isnet

To train on multiple GPUs, e.g. 8 GPUs, run the following command:

mim train mmsegmentation configs/isnet_r50-d8_8xb2-160k_cityscapes-512x1024.py --work-dir work_dirs/isnet --launcher pytorch --gpus 8

Testing commands

mim test mmsegmentation configs/isnet_r50-d8_8xb2-160k_cityscapes-512x1024.py --work-dir work_dirs/isnet --checkpoint ${CHECKPOINT_PATH}
Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
ISNet R-50-D8 512x1024 - - - 79.32 80.88 config model

Citation

@article{Jin2021ISNetII,
  title={ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation},
  author={Zhenchao Jin and B. Liu and Qi Chu and Nenghai Yu},
  journal={2021 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2021},
  pages={7169-7178}
}

Checklist

The progress of ISNet.

  • Milestone 1: PR-ready, and acceptable to be one of the projects/.

    • Finish the code
    • Basic docstrings & proper citation
    • Test-time correctness
    • A full README

  • Milestone 2: Indicates a successful model implementation.

    • Training-time correctness

  • Milestone 3: Good to be a part of our core package!

    • Type hints and docstrings
    • Unit tests
    • Code polishing
    • Metafile.yml

  • Move your modules into the core package following the codebase's file hierarchy structure.

  • Refactor your modules into the core package following the codebase's file hierarchy structure.