YOLOv5 Image Object Detection

This repository contains a Jupyter Notebook for performing object detection using the YOLOv5 model. YOLOv5 is a family of object detection architectures and models pretrained on the COCO dataset, allowing for fast and accurate detection of objects in images.

Getting Started

Prerequisites

Before you can run the code in this repository, ensure that you have the following installed on your system:

• Python 3.8 or higher
• pip (Python package installer)
• Visual Studio with Python support

Installation

1. Clone the YOLOv5 repository
   The first step is to clone the YOLOv5 GitHub repository, which contains the necessary code and pre-trained models for YOLOv5.

   git clone https://github.com/ultralytics/yolov5.git
   

2. Navigate to the YOLOv5 directory
   Change your current directory to the cloned repository.

   cd yolov5
   

3. Install the required dependencies
   Install the dependencies required to run the YOLOv5 model.

   pip install -r requirements.txt
   

Usage in Visual Studio

1. Open the Project

   • Open Visual Studio and go to File > Open > Folder....
   • Select the yolov5 directory you cloned earlier.

2. Run the Jupyter Notebook

   • In Visual Studio, navigate to the yolov5imgobjdet.ipynb file.
   • Open the notebook, and you will see an interactive interface where you can execute cells.
   • Follow the instructions in the notebook to perform object detection on images.

Directory Structure

• yolov5imgobjdet.ipynb: The main Jupyter Notebook for performing object detection.
• data/: Contains sample images and other data files used in the notebook.
• models/: Directory where you can store the YOLOv5 model weights.
• runs/detect/exp: Directory where the result are stored.

Notes

• The notebook is configured to work with the YOLOv5 model, and you may need to modify paths or configurations based on your specific environment.
• Ensure that your system's GPU has sufficient memory (4GB or more) if you plan to use GPU acceleration.

Acknowledgments

• YOLOv5 by Ultralytics is a state-of-the-art object detection model that has been widely adopted for various applications.

Contributing

• We welcome contributions to enhance this project. Please fork the repository and create a pull request with your changes. Ensure your code follows the project's coding standards and includes appropriate tests.

Contact

• For any questions or feedback, please reach out to [Ajay] at [ajayjnitt@gmail.com].