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ddpnet

https://github.com/mmgongzhu/ddpnet

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
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    .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (5.6%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: mmgongzhu
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 4.92 MB
Statistics
  • Stars: 1
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 9 months ago · Last pushed 9 months ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

1.Requirements

python conda create --name openmmlab python=3.8 -y conda activate openmmlab pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 pip install timm==0.6.13 pip install mmcv==2.0.0rc4 pip install opencv-python==4.11.0.86 pip install mmsegmentation==1.2.2

DDPNet is based on mmsegmentation and CGRSeg,The specific method for setting up the environment can be found in the official mmsegmentation documentation.

2.Checkpoint

  • The backbone network uses efficientformerV2, and the pre-training can be obtained directly from the official
  • The weights on ADE20K of our proposed DDPNet are obtained by clicking here
  • The weights on PASCAL-CONTEXT of our proposed DDPNet are obtained by clicking here

3.Traning ＆ Testing

  • ## traning

python python train.py local_configs/ddpseg/ddpseg_1×b16_160k_ade20k-512×512.py

  • ## Testing

python python test.py local_configs/ddpseg/ddpseg_1×b16_160k_ade20k-512×512.py ${CHECKPOINT_FILE}

Owner

  • Name: menghuang
  • Login: mmgongzhu
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - name: "MMSegmentation Contributors"
title: "OpenMMLab Semantic Segmentation Toolbox and Benchmark"
date-released: 2020-07-10
url: "https://github.com/open-mmlab/mmsegmentation"
license: Apache-2.0

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Dependencies

.github/workflows/deploy.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
.circleci/docker/Dockerfile docker
  • pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
docker/Dockerfile docker
  • pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
docker/serve/Dockerfile docker
  • pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
requirements/albu.txt pypi
  • albumentations >=0.3.2
requirements/docs.txt pypi
  • docutils ==0.16.0
  • myst-parser *
  • sphinx ==4.0.2
  • sphinx_copybutton *
  • sphinx_markdown_tables *
  • urllib3 <2.0.0
requirements/mminstall.txt pypi
  • mmcv >=2.0.0rc4,<2.2.0
  • mmengine >=0.5.0,<1.0.0
requirements/multimodal.txt pypi
  • ftfy *
  • regex *
requirements/optional.txt pypi
  • cityscapesscripts *
  • diffusers *
  • einops ==0.3.0
  • imageio ==2.9.0
  • imageio-ffmpeg ==0.4.2
  • invisible-watermark *
  • kornia ==0.6
  • nibabel *
  • omegaconf ==2.1.1
  • pudb ==2019.2
  • pytorch-lightning ==1.4.2
  • streamlit >=0.73.1
  • test-tube >=0.7.5
  • timm *
  • torch-fidelity ==0.3.0
  • torchmetrics ==0.6.0
  • transformers ==4.19.2
requirements/readthedocs.txt pypi
  • mmcv >=2.0.0rc1,<2.1.0
  • mmengine >=0.4.0,<1.0.0
  • prettytable *
  • scipy *
  • torch *
  • torchvision *
requirements/runtime.txt pypi
  • matplotlib *
  • numpy *
  • packaging *
  • prettytable *
  • scipy *
requirements/tests.txt pypi
  • codecov * test
  • flake8 * test
  • ftfy * test
  • interrogate * test
  • pytest * test
  • regex * test
  • xdoctest >=0.10.0 test
  • yapf * test
requirements.txt pypi
setup.py pypi