Lie Detector lets you monitor the heart rate and possible 'tells' of deception from any face, including live video calls or recordings.
Video demo and more info [available
Lie Detector uses OpenCV and MediaPipe's Face Mesh to perform real-time detect of facial landmarks from video input. It also uses FER for mood detection. From there, relative differences are calculated to determine significant changes in specific facial movements from a person's baseline, including their:
- Heart rate
- Blink rate
- Change in gaze
- Hand covering face
- Lip compression
Lie Detector can optionally include prompts based on a second video feed to better 'mirror' the original input.
Hit Q on the preview window to exit the resulting display frame, or
CTRL+C at the terminal to close the Python process.
Lie Detector is built for Python 3 and will not run on 2.x.
Optional flags:
--help- Display the below options--input- Choose a camera, video file path, or screen dimensions in the formx y width height- defaults to device0--landmarks- Set to any value to draw overlayed facial and hand landmarks--bpm- Set to any value to include a heart rate tracking chart--flip- Set to any value to flip along the y-axis for a selfie view--landmarks- Set to any value to draw detected body landmarks from MediaPipe--record- Set to any value to write the output to a timestamped AVI recording in the current folder--second- Secondary video input device for mirroring prompts (device number or path)--ttl- Number of subsequent frames to display a tell; defaults to 30
Example usage:
python intercept.py -h- Show all argument optionspython intercept.py --input 2 --landmarks 1 --flip 1 --record 1- Camera device 2; overlay landmarks; flip; generate a recordingpython intercept.py -i "/Downloads/shakira.mp4" --second 0- Use video file as input; use camera device 0 as secondary input for mirroring feedback