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

Clone the repository
Install the required packages using the following command:

pip install -r requirements.txt

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')