Namalytics is an amazing app that was created as a final project for the Computer Vision course. It's not just about doing an assignment, it's also a great opportunity to have some fun in the world of technology and to improve my portfolio!
It's a simple yet crucial feature that enhances the efficiency of student identification processes within the campus environment. With the help of cutting-edge object detection technology, this application can ensure that every registered UPJ student's identity is accurately recognized and validated in real time.
This project would not have been completed without the contributions of our campus friends, thanks to:
| No | Name | Job |
|---|---|---|
| 1 | Rama Adityo | Programmer |
| 2 | M. Arya Yudhistira | Dataset Collector |
To keep this app running smoothly, we use a few different technologies. Some of them are:
Streamlit
This is the foundation for creating and managing web app of Python, or the look and feel of the application. With Streamlit, we can build an interface that is straightforward but stylish enough for users. The app works great, and it's also visually appealing!YOLO algorithm
YOLO is a state-of-the-art object detection algorithm known for its speed and accuracy. Leveraging YOLO, the application can quickly and reliably identify registered students from live video feeds, ensuring seamless performance even in dynamic campus environments.OpenCV
OpenCV helps in pre-processing and analyzing video feeds to enhance the accuracy of the detection system. From capturing real-time frames to integrating with YOLO, OpenCV ensures good image handling, enabling the application to maintain consistent and reliable results in real-time student identification.
To use this application, you need to do a few things to make it work:
git clone https://github.com/ramadityo/namalytics.gitFor Windows:
py -m venv .venv.venv\Scripts\activateFor Linux
python3 -m venv .venvsource .venv/bin/activatepip3 install -r requirements.txtstreamlit run app.pyThis project is licensed under the MIT License. See the LICENSE link for details.