MyUnattendedLuggage

Unattended Luggage Detection

This project aims to detect unattended luggage in airports and other public places. The project is implemented using YOLOv8 object and MiDaS for depth estimation.

Requirements

• Python 3.10 or later
• Torch 2.4.0

Installation

1. Clone the repository
2. Install the required packages using the following command:

pip install -r requirements.txt

1. If you have Nvidia GPU, make sure to install CUDA and a supported Torch version

Usage

Run the main.py file to start the application. Make sure to modify the main.py file to give it a path to a video to process. You can do this by modifiying the following line:

video_path = "path/to/video.mp4"

My Model

This model is a custom YOLO and DeepSORT tracker model for object tracking and unattended luggage detection.

Files Included

• yolov8x_custom_weights.pt: YOLOv8 custom weights.
• midas_weights.pth: Weights for the MiDaS depth estimation model.

Usage

You can use this model by loading the weights and running the provided script.

import torch
from ultralytics import YOLO
from deep_sort_realtime.deepsort_tracker import DeepSort

# Load the model
model = YOLO('yolov8x_custom_weights.pt')