A collection of 5th year computer engineering projects including hand-tracking demos using MediaPipe and OpenCV.
This repository contains a collection of 5th year computer engineering projects developed for teamwork and learning. The main focus is on AI and computer vision applications.
Hand-tracking demos using MediaPipe and OpenCV for gesture-based interfaces.
Future project folder for language translation applications.
Future project folder for machine learning experiments.
Testing and experimental code.
A wrapper class for MediaPipe Hands that provides:
process(frame, return_pixel_landmarks=False) - Process BGR OpenCV framesget_hands_landmarks() - Returns landmarks as (id, cx, cy) tuples per handdraw_landmarks(frame) - Draw landmarks onto framesclose() - Release tracker resourcesUses HandTracker with a rule-based recognizer to map simple hand poses to speech via pyttsx3 text-to-speech engine.
Maps thumb-index finger distance to system volume. On Windows with pycaw installed, it directly controls system volume; otherwise displays mapped volume on-screen.
Install dependencies (recommended to use a virtual environment):
python -m pip install -r requirements.txt
For Windows volume control, additionally install:
python -m pip install pycaw comtypes
# Sign to Voice demo python sign_to_voice.py # Volume control demo python volume-hand-controle.py