This repository contains the code for an Object Detection project. Object detection is a computer vision technique that involves locating and classifying objects in images or video. This project aims to implement object detection using [insert technique or framework here, e.g., YOLO, SSD, Faster R-CNN, etc.].

Below are the main projects and chapters covered in this repository.

• This project focuses on detecting and counting cars in images or video streams.
• Implementation: Using YOLOv8, the system identifies cars in a given image or video and provides a count of the total number of cars detected.

• This project involves detecting and counting people in images or video streams.
• Implementation: YOLOv8 is utilized to identify individuals in images or video footage and provides a count of the total number of people detected.

• This project aims to detect whether individuals are wearing Personal Protective Equipment (PPE) such as helmets, vests, and goggles.
• Implementation: YOLOv8 is employed to identify PPE items in images or video feeds, ensuring safety compliance.

• This project focuses on identifying and recognizing poker hands in images or video streams.
• Implementation: Utilizing YOLOv8, the system identifies and classifies various poker hands present in an image or video.

• This chapter provides instructions on how to run the YOLOv8 algorithm for object detection tasks.
• Implementation: Step-by-step guide on installing dependencies, configuring the environment, and executing YOLOv8 for object detection.

• This chapter explains how to utilize YOLOv8 with a webcam for real-time object detection.
• Implementation: Instructions on setting up the webcam, configuring YOLOv8, and running real-time object detection on live video feeds.

• Object detection model implementation
• Training pipeline
• Evaluation scripts
• Pre-trained models
• Documentation

• Python >= 3.8

• cvzone (version 1.5.6)
• ultralytics (version 8.0.26)
• hydra-core (version >= 1.2.0)
• matplotlib (version >= 3.2.2)
• numpy (version >= 1.18.5)
• opencv-python (version 4.5.4.60)
• Pillow (version >= 7.1.2)
• PyYAML (version >= 5.3.1)
• requests (version >= 2.23.0)
• scipy (version >= 1.4.1)
• torch (version >= 1.7.0)
• torchvision (version >= 0.8.1)
• tqdm (version >= 4.64.0)
• filterpy (version 1.4.5)
• scikit-image (version 0.19.3)
• lap (version 0.4.0)

You can install these dependencies using pip:

pip install -r requirements.txt

1. Clone the repository:

git clone https://github.com/Abdallah-707/Object-Detection.git

This project is licensed under the MIT License - see the LICENSE file for details.