Science Score: 54.0%

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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
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    Links to: zenodo.org
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    Low similarity (15.9%) to scientific vocabulary
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Repository

Basic Info
  • Host: GitHub
  • Owner: shashankguptta
  • License: agpl-3.0
  • Language: Python
  • Default Branch: main
  • Size: 12.8 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme Contributing License Citation

README.md

YOLOv5 CI YOLOv5 Citation Docker Pulls Discord
Run on Gradient Open In Colab Open In Kaggle


YOLOv5 🚀 is the world's most loved vision AI, representing Ultralytics open-source research into future vision AI methods, incorporating lessons learned and best practices evolved over thousands of hours of research and development.

We hope that the resources here will help you get the most out of YOLOv5. Please browse the YOLOv5 Docs for details, raise an issue on GitHub for support, and join our Discord community for questions and discussions!

YOLOv5 Object Detection This repository contains an implementation of YOLOv5, a state-of-the-art object detection model, for detecting objects in images. YOLOv5 is known for its high performance and accuracy in real-time object detection tasks. Features

YOLOv5 implementation for object detection
Support for PyTorch, ONNX, CoreML, and TFLite
Easy integration with other frameworks and tools
Efficient and fast object detection capabilities

Prerequisites

Python installed on your system
PyTorch, ONNX, CoreML, and TFLite libraries

Installation

Clone the repository to your local machine:

git clone https://github.com/your-username/yolov5-object-detection.git

Navigate to the project directory:

cd yolov5-object-detection

Usage

Run the YOLOv5 object detection script:

python detect_objects.py

The script will use the YOLOv5 model to detect objects in images.
Customize the script to work with your specific dataset or requirements.

Example

python detect_objects.py --image image.jpg

Contributing

If you have any suggestions, improvements, or find any issues, feel free to open an issue or submit a pull request.

YOU CAN ASSES FULL DOCUMENTION ON YOLOV5 ON ORIGNAL BASIS https://github.com/ultralytics/yolov5

Owner

  • Name: SHASHANK GUPTTA
  • Login: shashankguptta
  • Kind: user
  • Location: INDIA

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
requirements.txt pypi