Can you write a report on Object Counting in Different Regions

Using Intel RealSense Cam with code to implement this:

Introduction

This capstone project involves the implementation of a sophisticated object counting system using the Intel

RealSense camera and the advanced object detection model, Ultralytics YOLOv$8.$ The project is designed to

provide students with hands$-$on experience in integrating computer vision technologies with web

applications, specifically focusing on real$-$time object detection and counting.

Task Definition

The primary task is to develop a system that counts cars in different regions of a parking

lot using a RealSense camera connected to a computer. The system should:

$$ Divide the parking lot into different sections, each represented by a rectangular box.

$$ Count the number of cars in each region in real$-$time.

$$ Simultaneously increment the total number of cars entering and leaving.

$$ Segment each car using segmentation techniques.

$$ Label each car type distinctly.

$$ Maintain a total count categorized by car type as well as an overall total count.

GUIDING QUESTIONS

Summary of Guiding Questions

The project is broken down into three practical experiments, each with specific objectives and tasks:

$1.$ Project Preparations:

$$ Setting up a Flask application.

$$ Integrating the Intel RealSense camera for live streaming.

$$ Adding basic functionalities like thresholding and control features.

$2.$ Integrating YOLOv$8$:

$$ Installing YOLOv$8$ and testing it with the MS COCO dataset.

$$ Integrating YOLOv$8$ into the Flask application for real$-$time object detection.

$$ Displaying detection data clearly within the application.

$3.$ Training a Custom Model:

$$ Training a custom YOLOv$8$ model with a custom dataset.

$$ Replacing the default model in the Flask application with the custom$-$trained model.

$$ Testing and making final adjustments to ensure accurate performance.

More Information

For a detailed step$-$by$-$step guide on how to carry out each practical experiment, including the setup

procedures, code snippets, and testing methods, please refer to the practical guide. Each practical and its

respective steps are properly defined to ensure clear and comprehensive understanding and execution.