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object-detector

Object-Detector-YOLOv5 is a robust object detection system leveraging the YOLOv5 (You Only Look Once) model. It identifies and classifies objects in images, videos, and live streams with high accuracy and real-time performance. This project is adaptable for a variety of object detection tasks and supports both pre-trained models and custom training

https://github.com/hanish9193/object-detector

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
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    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.7%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Object-Detector-YOLOv5 is a robust object detection system leveraging the YOLOv5 (You Only Look Once) model. It identifies and classifies objects in images, videos, and live streams with high accuracy and real-time performance. This project is adaptable for a variety of object detection tasks and supports both pre-trained models and custom training

Basic Info
  • Host: GitHub
  • Owner: hanish9193
  • License: agpl-3.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 16.4 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Citation

README.md

🚀 YOLOv5 Object Detector

An advanced object detection system built using the YOLOv5 model. This project can identify and classify objects in images and videos with high accuracy and real-time performance.

📷 Features

  • 🟢 Pre-trained YOLOv5 Model for fast and accurate detection
  • 📊 Supports detection in images, videos, and live streams
  • 🧰 Customizable for training on new datasets
  • 📈 Outputs detection results with bounding boxes and confidence scores
  • 🏎️ Optimized for speed and works on both CPU and GPU

📂 Project Structure

├── data/ # Dataset and input files ├── models/ # YOLOv5 model configuration ├── runs/ # Output folder for detections ├── detect.py # Main detection script ├── train.py # Model training script └── README.md # Project documentation

🔧 Installation

  1. Clone the repository:

bash git clone https://github.com/hanish9193/Object-Detector.git cd Object-Detector

  1. Set up a virtual environment (optional but recommended):

bash python -m venv venv source venv/bin/activate # For Linux/macOS venv\Scripts\activate # For Windows

  1. Install required packages:

bash pip install -r requirements.txt

▶️ Usage

1. Run Object Detection on Images

bash python detect.py --source path/to/image.jpg --weights yolov5s.pt

2. Run Object Detection on Videos

bash python detect.py --source path/to/video.mp4 --weights yolov5s.pt

3. Real-Time Detection (Webcam)

bash python detect.py --source 0 --weights yolov5s.pt

📊 Training Your Own Model

  1. Prepare your dataset following the YOLO format.
  2. Use the train.py script:

bash python train.py --data custom_dataset.yaml --epochs 50 --weights yolov5s.pt

📜 Requirements

  • Python 3.8+
  • PyTorch
  • OpenCV
  • YOLOv5

📌 Example Output

Detection Output

🤝 Contributing

Contributions are welcome! Feel free to open an issue or submit a pull request.

📄 License

This project is licensed under the AGPL-3.0 License.

📬 Contact

If you have any questions or issues, reach out via GitHub Issues.

Owner

  • Name: Hanish
  • Login: hanish9193
  • 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"

GitHub Events

Total
  • Issue comment event: 4
  • Public event: 1
  • Pull request event: 3
  • Create event: 4
Last Year
  • Issue comment event: 4
  • Public event: 1
  • Pull request event: 3
  • Create event: 4

Dependencies

.github/workflows/ci-testing.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v5 composite
  • slackapi/slack-github-action v2.0.0 composite
.github/workflows/cla.yml actions
  • contributor-assistant/github-action v2.6.1 composite
.github/workflows/docker.yml actions
  • 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
.github/workflows/format.yml actions
  • ultralytics/actions main composite
.github/workflows/links.yml actions
  • actions/checkout v4 composite
  • ultralytics/actions/retry main composite
.github/workflows/merge-main-into-prs.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v5 composite
.github/workflows/stale.yml actions
  • actions/stale v9 composite
utils/docker/Dockerfile docker
  • pytorch/pytorch 2.0.0-cuda11.7-cudnn8-runtime build
utils/google_app_engine/Dockerfile docker
  • gcr.io/google-appengine/python latest build
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
utils/google_app_engine/additional_requirements.txt pypi
  • Flask ==2.3.2
  • gunicorn ==22.0.0
  • pip ==23.3
  • werkzeug >=3.0.1
  • zipp >=3.19.1