Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (5.1%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: Liu-Hong-Xin-1219
- License: mit
- Language: Python
- Default Branch: master
- Size: 2.04 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
PCB实例分割
本项目是一个PCB元件实例分割项目, 使用了pybind11,使得其可以在cpp环境下运行. 模型使用onnx格式
环境配置
本项目的环境配置和金线分割一致
1. CUDA & Cudnn 测试可运行版本
| CUDA Version | Python Version | Cudnn Version | GPU | | ------------ | -------------- | ------------- | -------- | | CUDA 11.8 | 3.8.10 | 8.x | RTX 3080 |
2. Python 依赖安装
bash
cd PCB_Seg
pip install onnx==1.17.0
pip install onnxruntime-gpu==1.18.1
pip install torch==2.0.0+cu118
pip install opencv-python
pip install -e .
3. 环境验证
3.1 编译项目
bash
cd PCB_Seg
rm -rf build
mkdir build && cd build
cmake ..
make -j
3.2 运行项目
bash
./PCB_Seg
以上步骤运行了models/synpcbseg.onnx模型, 分割了图片input/demopcb.png, 分割的可视化结果保存在build/runs/predict/exp/visuals/1.jpg之中.
4. 其他资源
模型权重文件 models/synpcbseg.pt,models/synpcbseg.onnx
示例用pcb图片 input/demopcb.png
使用demo 请参考source/main.cpp的main()
纯python demo mytest/mainapi.py 在项目根目录运行pip install -e . 然后使用下面代码，即可调用python的api infer()
License
This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License - see the LICENSE file for details.
This means: - ✅ You can freely use this code for non-commercial purposes - ✅ You can modify and share this code - ❌ You cannot use this code for commercial purposes - ❌ You cannot sublicense or sell this code
Owner
- Login: Liu-Hong-Xin-1219
- Kind: user
- Repositories: 1
- Profile: https://github.com/Liu-Hong-Xin-1219
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this package, please consider citing it."
authors:
- family-names: "Akyon"
given-names: "Fatih Cagatay"
- family-names: "Cengiz"
given-names: "Cemil"
- family-names: "Altinuc"
given-names: "Sinan Onur"
- family-names: "Cavusoglu"
given-names: "Devrim"
- family-names: "Sahin"
given-names: "Kadir"
- family-names: "Eryuksel"
given-names: "Ogulcan"
title: "SAHI: A lightweight vision library for performing large scale object detection and instance segmentation"
preferred-citation:
type: article
title: "Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection"
doi: 10.1109/ICIP46576.2022.9897990
url: https://ieeexplore.ieee.org/document/9897990
journal: 2022 IEEE International Conference on Image Processing (ICIP)
authors:
- family-names: "Akyon"
given-names: "Fatih Cagatay"
- family-names: "Altinuc"
given-names: "Sinan Onur"
- family-names: "Temizel"
given-names: "Alptekin"
year: 2022
start: 966
end: 970
GitHub Events
Total
- Push event: 2
- Create event: 2
Last Year
- Push event: 2
- Create event: 2
Dependencies
- actions/cache v4 composite
- actions/checkout v4 composite
- actions/setup-python v5 composite
- actions/cache v4 composite
- actions/checkout v4 composite
- actions/setup-python v5 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- click *
- fire *
- opencv-python <=4.10.0.84
- pillow >=8.2.0
- pybboxes ==0.1.6
- pyyaml *
- requests *
- shapely >=2.0.0
- terminaltables *
- tqdm >=4.48.2