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dynamic-lightweight-upsampling

https://github.com/fu0511/dynamic-lightweight-upsampling

Science Score: 44.0%

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Repository

Basic Info
  • Host: GitHub
  • Owner: Fu0511
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 1.3 GB
Statistics
  • Stars: 7
  • Watchers: 1
  • Forks: 1
  • Open Issues: 1
  • Releases: 0
Created almost 2 years ago · Last pushed about 1 year ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

DLU implementation in Pytorch

Code for the paper:

[Lighten CARAFE: Dynamic Lightweight Upsampling with Guided Reassemble Kernels]

Oral at ICPR 2024,
Authors:
Ruigang Fu, Qingyong Hu, Xiaohu Dong, Yinghui Gao, Biao Li and Ping Zhong

Framework

Requirements

1. Environment:

The requirements are exactly the same as mmdetection(https://github.com/open-mmlab/mmdetection). We tested on the following settings:

  • python 3.8
  • cuda 10.1
  • pytorch 1.8.1+cu101
  • torchvision 0.9.1+cu101
  • mmcv 2.1.0

setup conda create -n dlu python=3.8 -y source activate dlu conda activate dlu pip install torch==1.8.1+cu101 torchvision==0.9.1+cu101 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html pip install -U openmim mim install mmengine mim install "mmcv>=2.0.0" git clone https://github.com/Fu0511/Dynamic-Lightweight-Upsampling.git cd mmdetection pip install -v -e .

2. Data:

The folder data should be like this: data ├── coco │   ├── annotations │   ├── train2017 │   ├── val2017 │   ├── test2017

Training

Use the following commands to train a model.

```train

Single GPU

python tools/train.py ${CONFIG_FILE}

Multi GPU distributed training

./tools/disttrain.sh ${CONFIGFILE} ${GPUNUM} `` Config files in our experiments are under./custom/config/FPN/. -./custom/config/FPN/cococustomdlu.py: FPN model with DLU as its upsampling operation. -./custom/config/FPN/cococustomcarafe: FPN model with carafe as its upsampling operation. -./custom/config/FPN/cocobaseline_bilinear`: FPN model with bilinear as its upsampling operation.

Results

The main results on coco val set:

| Method | AP | Additional Model Size| | -------- | ----- | -------------------- | | Bilinear | 37.5 | -- | | CARAFE | 38.6 | +1.2MB | | DLU | 38.6 | +0.6MB |

If these codes are useful to you, please cite our work: @misc{fu2024Lighten, title={Lighten CARAFE: Dynamic Lightweight Upsampling with Guided Reassemble Kernels}, author={Ruigang Fu and Qingyong Hu and Xiaohu Dong and Yinghui Gao and Biao Li and Ping Zhong}, year={2024}, eprint={2410.22139}, archivePrefix={arXiv}, primaryClass={cs.CV} }

Owner

  • Login: Fu0511
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - name: "MMDetection Contributors"
title: "OpenMMLab Detection Toolbox and Benchmark"
date-released: 2018-08-22
url: "https://github.com/open-mmlab/mmdetection"
license: Apache-2.0

GitHub Events

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Dependencies

.github/workflows/deploy.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 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
docker/serve_cn/Dockerfile docker
  • pytorch/pytorch ${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel build
requirements/albu.txt pypi
  • albumentations >=0.3.2
requirements/build.txt pypi
  • cython *
  • numpy *
requirements/docs.txt pypi
  • docutils ==0.16.0
  • myst-parser *
  • sphinx ==4.0.2
  • sphinx-copybutton *
  • sphinx_markdown_tables *
  • sphinx_rtd_theme ==0.5.2
  • urllib3 <2.0.0
requirements/mminstall.txt pypi
  • mmcv >=2.0.0rc4,<2.2.0
  • mmengine >=0.7.1,<1.0.0
requirements/multimodal.txt pypi
  • fairscale *
  • jsonlines *
  • nltk *
  • pycocoevalcap *
  • transformers *
requirements/optional.txt pypi
  • cityscapesscripts *
  • emoji *
  • fairscale *
  • imagecorruptions *
  • scikit-learn *
requirements/readthedocs.txt pypi
  • mmcv >=2.0.0rc4,<2.2.0
  • mmengine >=0.7.1,<1.0.0
  • scipy *
  • torch *
  • torchvision *
  • urllib3 <2.0.0
requirements/runtime.txt pypi
  • matplotlib *
  • numpy *
  • pycocotools *
  • scipy *
  • shapely *
  • six *
  • terminaltables *
  • tqdm *
requirements/tests.txt pypi
  • asynctest * test
  • cityscapesscripts * test
  • codecov * test
  • flake8 * test
  • imagecorruptions * test
  • instaboostfast * test
  • interrogate * test
  • isort ==4.3.21 test
  • kwarray * test
  • memory_profiler * test
  • nltk * test
  • onnx ==1.7.0 test
  • onnxruntime >=1.8.0 test
  • parameterized * test
  • prettytable * test
  • protobuf <=3.20.1 test
  • psutil * test
  • pytest * test
  • transformers * test
  • ubelt * test
  • xdoctest >=0.10.0 test
  • yapf * test
requirements/tracking.txt pypi
  • mmpretrain *
  • motmetrics *
  • numpy <1.24.0
  • scikit-learn *
  • seaborn *
requirements.txt pypi
setup.py pypi