Labeler demo

Installing and Running

git lfs install
git clone https://github.com/Tom-stack3/Labeler_demo.git
cd Labeler_demo
pip install -r requirements.txt
python app.py

• Make sure you have a working camera connected to your device.

• If the following command doesn't work:

  $ pip install -r requirements.txt
  
  'pip' is not recognized..

  Then use instead:

  python -m pip install -r requirements.txt

Output

All the labeled images and a log file are saved locally in the output folder, which will be created automatically. In order to protect the user's privacy, the person's eyes detected in a captured image are censored, before the image is saved locally.

An example for three images generated from a camera capture, which are then saved locally by the script:

^{The example was generated from this image.}

Performance

Between capture to capture, the frame freezes, meaning the script is proccessing the image in the background. It usually takes less than 4 second in total to proccess the image, but it depends on your device. Usually the most time-consuming part is the depth analyzer.

Acknowledgements

• The point detection uses a 2D Pose Estimation model, published in this paper.
• The depth analysis uses the MiDaS model.