This is a Face Mesh Detection Web App made using a Python library called Streamlit used to make Custom Data Science & Machine Learning Web Apps. The Face Mesh is achieved through the Cross-Platform Machine Learning Solutions Library called Mediapipe loaded using OpenCV Python. The User can choose between two App Modes: Image Mode & Video Mode. Depending on the mode selected, the User can either upload an Image File or a Video File, apply the Face Detection Mesh, and view the resulting output on the Main Page. Additionally, the User has the option to enter the Number of faces they would like to detect on an Image or Video and control the Detection Confidence, the Tracking Confidence, the Mesh Drawing Thickness, and the Mesh Circle Radius.
https://share.streamlit.io/mohdalibn/face-mesh-detection-web-app/main/FaceMeshWebApp.py
CLICK HERE TO OPEN A LIVE DEMO OF THE APP ON YOUR BROWSER
Install the following Python libraries in your Virtual Environment using PIP.
Note: The library names are CASE-SENSITIVE for PIP installations below. Make sure your type them correctly.
Install Streamlit for Python
pip install streamlitInstall Mediapipe for Python
pip install mediapipeInstall OpenCV for Python
pip install opencv-pythonInstall OpenCV Contrib for Python
pip install opencv-contrib-pythonInstall Numpy for Python
pip install numpyInstall Pillow for Image Processing in Python
pip install PillowDownload a copy of this repository onto your local machine and extract it into a suitable folder.
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Install all the required Python libraries mentioned above.
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Open a Command Prompt/Terminal in the Root Directory of the Project.
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Type the following command in the terminal to start an instance of the Streamlit App.
streamlit run FaceMeshWebApp.py- Enjoying using the App!