weeddetection-yolov5-custom
Science Score: 44.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○DOI references
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○Scientific vocabulary similarity
Low similarity (5.3%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: yashghadale
- License: agpl-3.0
- Language: Python
- Default Branch: main
- Size: 1 MB
Statistics
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Weed Detection using UAV and YOLOv5 + ECA + BottleneckCSP + GhostConv
This project improves YOLOv5s for Weed Detection in Agricultural Fields using drone (UAV) images. We enhance the base architecture by integrating custom modules like:
- Conv_ECA — Efficient Channel Attention inside convolution
- BottleneckCSP — Improved feature extraction
- GhostConv — Lightweight computation for faster inference
Project Structure
```text WeedDetection-YOLOv5-Custom/ ├── models/ │ ├── common.py # Custom layers (ConvECA, BottleneckCSP, GhostConv) │ └── yolov5s.yaml # Modified YOLOv5s model architecture │ ├── data/ │ └── agriweed.yaml # Dataset config (classes, paths) │ ├── runs/ │ └── train/ │ └── yolov5seca/ # Training logs (plots, PR/mAP curves, weights) │ ├── detect.py # Inference script └── README.md # Project documentation
Key Modifications
- Replaced all standard Conv layers with Conv_ECA
- Added Efficient Channel Attention (ECA) for channel-wise feature refinement
- Integrated BottleneckCSP blocks
- Maintained detection heads and neck structure as in YOLOv5s
- Trained on the AgriWeed Dataset for precision weed classification
Training (example)
```bash !python train.py \ --img 640 \ --batch 2 \ --epochs 1 \ --data /content/agriweed.yaml \ --cfg models/yolov5s.yaml \ --weights '' \ --name ghostconv_check
Owner
- Login: yashghadale
- Kind: user
- Repositories: 1
- Profile: https://github.com/yashghadale
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"
GitHub Events
Total
- Watch event: 1
- Issue comment event: 2
- Push event: 5
- Create event: 3
Last Year
- Watch event: 1
- Issue comment event: 2
- Push event: 5
- Create event: 3
Dependencies
- actions/checkout v4 composite
- actions/setup-python v5 composite
- astral-sh/setup-uv v6 composite
- slackapi/slack-github-action v2.1.0 composite
- contributor-assistant/github-action v2.6.1 composite
- actions/checkout v4 composite
- docker/build-push-action v6 composite
- docker/login-action v3 composite
- docker/setup-buildx-action v3 composite
- docker/setup-qemu-action v3 composite
- ultralytics/actions main composite
- actions/checkout v4 composite
- ultralytics/actions/retry main composite
- actions/checkout v4 composite
- actions/setup-python v5 composite
- actions/stale v9 composite
- pytorch/pytorch 2.0.0-cuda11.7-cudnn8-runtime build
- gcr.io/google-appengine/python latest build
- 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 >=8.2.64
- 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
- Flask ==2.3.2
- gunicorn ==23.0.0
- pip ==23.3
- werkzeug >=3.0.1
- zipp >=3.19.1