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tunnelcrack

使用yolov5训练隧道裂缝识别

https://github.com/zhany0/tunnelcrack

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (0.7%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

使用yolov5训练隧道裂缝识别

Basic Info
  • Host: GitHub
  • Owner: zhany0
  • License: agpl-3.0
  • Language: Python
  • Default Branch: main
  • Size: 3.43 MB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme Contributing License Citation

README.md

tunnelcrack

使用yolov5训练隧道裂缝识别 1、在pycharm终端输入 pip install -r requirements.txt 加载依赖库 2、打开train.py，shift+F5开始训练 3、训练结果保存在runs文件夹中 4、训练图片和标签保存在datasets中 5、使用detect推理你的图片集

Owner

  • Login: zhany0
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
preferred-citation:
  type: software
  message: If you use YOLOv5, please cite it as below.
  authors:
  - family-names: Jocher
    given-names: Glenn
    orcid: "https://orcid.org/0000-0001-5950-6979"
  title: "YOLOv5 by Ultralytics"
  version: 7.0
  doi: 10.5281/zenodo.3908559
  date-released: 2020-5-29
  license: AGPL-3.0
  url: "https://github.com/ultralytics/yolov5"

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Dependencies

pyproject.toml pypi
  • matplotlib >=3.3.0
  • numpy >=1.22.2
  • opencv-python >=4.6.0
  • pandas >=1.1.4
  • pillow >=7.1.2
  • psutil *
  • py-cpuinfo *
  • pyyaml >=5.3.1
  • requests >=2.23.0
  • scipy >=1.4.1
  • seaborn >=0.11.0
  • thop >=0.1.1
  • torch >=1.8.0
  • torchvision >=0.9.0
  • tqdm >=4.64.0
  • ultralytics >=8.1.47
requirements.txt pypi
  • PyYAML >=5.3.1
  • gitpython >=3.1.30
  • matplotlib >=3.3
  • numpy >=1.23.5
  • opencv-python >=4.1.1
  • pandas >=1.1.4
  • pillow >=10.3.0
  • psutil *
  • requests >=2.32.2
  • scipy >=1.4.1
  • seaborn >=0.11.0
  • setuptools >=70.0.0
  • thop >=0.1.1
  • torchvision >=0.9.0
  • tqdm >=4.66.3