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ldxray-mmdetection

https://github.com/suzipei/ldxray-mmdetection

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
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    Scientific vocabulary similarity
    Low similarity (12.7%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: SuZipei
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 12.9 MB
Statistics
  • Stars: 4
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Created about 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

Introduction

Our project extends the MMDetection framework to specialize in dual-view X-ray imaging. Unlike single-view datasets, dual-view imaging captures objects from both vertical and side perspectives, enhancing detection accuracy by reducing occlusions and providing more comprehensive views of the objects.

For more details, you can view our LDXray dataset introduction here.

How To Run

First, install our project following these steps:

bash git clone https://github.com/SuZipei/LDXray-mmdetection.git cd LDXray-mmdetection-main pip install -v -e .

For more detailed installation instructions, please refer to the installation guide.

Second, download our LDXray dataset and place it in the LDXray/dual-view directory.

We provide a function Load2ImageFromFiles in mmdet/datasets/transforms/loading.py to load dual-view images from the LDXray dataset. Additionally, we have rewritten ImgDataPreprocessor in mmdet/models/data_preprocessors/data_preprocessor.py to normalize dual-view data.

Third, write a configuration file for your model. Examples of configuration files used in our research can be found in LDXray/config.

Finally, train or test your model. Please refer to the train and test guide for detailed instructions.

Citation

Please note that our dataset is built upon the MMDetection framework, please cite the MMDetection framework as follows: plaintext @article{mmdetection, title = {{MMDetection}: Open MMLab Detection Toolbox and Benchmark}, author = {Chen, Kai and Wang, Jiaqi and Pang, Jiangmiao and Cao, Yuhang and Xiong, Yu and Li, Xiaoxiao and Sun, Shuyang and Feng, Wansen and Liu, Ziwei and Xu, Jiarui and Zhang, Zheng and Cheng, Dazhi and Zhu, Chenchen and Cheng, Tianheng and Zhao, Qijie and Li, Buyu and Lu, Xin and Zhu, Rui and Wu, Yue and Dai, Jifeng and Wang, Jingdong and Shi, Jianping and Ouyang, Wanli and Loy, Chen Change and Lin, Dahua}, journal = {arXiv preprint arXiv:1906.07155}, year = {2019} }

License

  • For academic and non-commercial use only
  • Apache License 2.0

Owner

  • Name: Guo Yuzhe
  • Login: SuZipei
  • 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

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  • xyb1314 (1)
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Dependencies

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