For Facedetection we are using Google Mediapipe. Link here. From this we are using the solutions Face Landmarker and Hand Landmarker. The canonical Face Landmark Model is shown here: Canonical Face Model. The model, used here, can be found on mediapipe solutions. The streamlit layout was derived from mpolinowski gitub. The algo development has been strongly supported be my best coworker, ChatGPT 4.0. The software is licensed by Apache License Version 2.0, January 2004.
Python Version used: 3.11.4
A virtual environment is a Python environment such that the Python interpreter, libraries and scripts installed into it are isolated from those installed in other virtual environments.
Prerequisites: Installation of the latest Python version from here:
- https://www.python.org/downloads/windows/ and and the Pip installer from here:
- https://phoenixnap.com/kb/install-pip-windows Then Install pyenv for Windows
pip install pyenv-win
- Install and update dependencies:
sudo apt update -y
sudo apt install -y make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm libncurses5-dev libncursesw5-dev xz-utils tk-dev libffi-dev liblzma-dev python-openssl git
- Prerequisites: Installation of the latest Pyenv version from here:
curl https://pyenv.run | bash
Update .bashrc:
echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bashrc echo 'export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bashrc echo -e 'if command -v pyenv 1>/dev/null 2>&1; then\n eval "$(pyenv init -)"\nfi' >> ~/.bashrc
Setting up the Virtual Environment: (1) Check pyenv version
pyenv versions
(2) Install Python
pyenv install 3.11.4
(3) Set this version local
pyenv local 3.11.4
(4) Install virtualvenv
python -m pip install virtualenv
(5) Create your environment
pyenv virtualenv 3.11.4 visionai
pyenv activate visionai
mkdir ~/workspace/
pip install -r requirements.txt
cd ~/workspace/VisualAI
streamlit run facedetection.py
Installing Dependencies: After activating the environment:
pip install -r requirements.txt
streamlit run facedetection.py
Installing Dependencies: After activating the environment:
pip install -r requirements.txt
Startup Screen
- It starts up with image processing. You can upload images from ./images/persons. Some examples can be found here. An evaluation document can be found here drvmonpics.doc
- Selecting video, a demo video is started. You can also upload videos form ./video/persons. If pressing the webcam button, the frames of a USB Webcam are shown and processed.
Demo Video
- To see the application in action, check out our demo video: View Demo
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