Object Detection With YOLOv8 Algorithm

This repository is the finished product of my final project in college that combines object detection using YOLOv8, an object detection algorithm, and Streamlit, a popular Python framework for creating interactive web applications. This project has four different detection modes, including realtime mode, detection mode from YouTube URLs, as well as detection mode from videos and static images.

WebApp Demo

Thanks to Streamlit team for providing cloud uploads so that I can make this webApp more accessible to the general public.

This app is up and running on Streamlit cloud server!!! You can check the demo of this web application on this link Object Detection With YOLOv8 Algorithm

Requirements

Python 3+
YOLOv8
Streamlit

pip install ultralytics streamlit pytube

Installation

Clone the repository: git clone https://github.com/CodingMantras/yolov8-streamlit-detection-tracking.git
Change to the repository directory: cd yolov8-streamlit-detection-tracking
Create weights, videos, and images directories inside the project.
Download the pre-trained YOLOv8 weights from (https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt) and save them to the weights directory in the same project.
Or if you have a model created with yolov8, you can save to the weights directory in the same project.

Usage

Run the app with the following command: streamlit run app.py
The app will be opened in a new browser window.

Detection on images

The default image with its objects-detected image is displayed on the main page.
Select a source. (radio option selection Image).
Upload an image by clicking on the "Browse files" button.
Click the Deteksi button to run the object detection algorithm on the uploaded image with the selected confidence threshold.
The output with objects detected will be displayed on the page.

Detection in Videos

I have two options for video detection, namely using the videos that I have prepared in this project, or uploading them myself
If you choose to upload the video yourself, then please select the upload tab
After The preview video has been displayed, you can click the Deteksi button then the detection results will be displayed
If you choose to use a video that I have prepared, you can select the sumber asal tab
Then you have to choose 1 of the 4 videos that have been prepared
Click on Deteksi button and detection will start on the selected video.

Detection on YouTube Video URL

Select the source as YouTube
Copy paste the url inside the text box.
The detection task will start on the YouTube video url

Acknowledgements

This app uses YOLOv8 for object detection algorithm and Streamlit library for the user interface.

Please contribute to the optimisation of this website and to gain in-depth knowledge. Hit star ⭐ if you like this repo!!!

gabrieladvent / thesis-web