This is a face recognition application built using Python, Face-Recognition API and Streamlit framework. The app allows users to upload an image containing faces and performs face recognition using the face recognition library.
- Face detection and recognition
- Multi-face recognition
- Option to display recognized faces
- User-friendly interface
- Python 3.9
- Streamlit 1.22.0
- face_recognition
├───dataset
│ │───ID_Name.jpg
│ │───...
├───pages
│ ├───1_🔧_Updating.py
│ └───2_💾_Database
├───Tracking.py
│───utils.py
├───config.yaml
├───requirements.txt
├───packages.txt
└───README.md
- dataset: contains images of people to be recognized. The file name format is ID_Name.jpg.
For example, 1_Elon_Musk.jpg, 2_Jenna_Ortega.jpg, 3_Bill_Gates.jpg, etc.
It is freely to use jpg, jpeg or png format. - pages: contains the code for each page of the app. If you want to add more pages, you can create a new file which format is
Order_Icon_Pagename
in this folder, or just no-icon page with formatOrder_Pagename
. - Tracking.py: home page of the app, using for tracking real-time using webcam and picture.
- utils.py: contains the functions utilized by the app.
- config.yaml: contains the configuration for the app such as path of dataset dir and prompt messages.
- requirements.txt: contains the dependencies for the app.
- packages.txt: contains the packages for the app used to deploy on Streamlit Cloud.
- Clone the repository
git clone https://github.com/datct00/Face-recognition-app-using-Streamlit.git
cd Face-recognition-app-using-Streamlit
- Install the dependencies
pip install -r requirements.txt
- Run the app
streamlit run Tracking.py
- Tracking real-time using webcam
- Tracking using a image file
- Updating database (adding, deleting and updating)
- Viewing the database
-
Deployed app on Streamlit Cloud. Click here to watch a demo of the app.
If you have any questions, feel free to contact me via email: [email protected]