Desktop computer vision project

Real-time facial recognition with enrollment, persistence, and smooth camera rendering.

This project ships a complete Python CustomTkinter application using OpenCV and face_recognition. It handles webcam errors, image upload enrollment, SQLite persistence, frame skipping, and threaded recognition.

Download app code

Project files

Download the source files below or read the included README for OS-specific dlib prerequisites.

README.mdSetup, prerequisites, and run guide requirements.txtPinned Python dependencies facedesk_app.pyComplete CustomTkinter + OpenCV app

Implementation breakdown

What is included

The desktop application is structured around camera capture, durable enrollment storage, and a background recognition pipeline.

Setup instructions

Create a Python 3.10 or 3.11 virtual environment, install the requirements, then run the desktop script. The app creates a local SQLite database and registered face image folder on first launch.

python -m venv .venv && source .venv/bin/activate && pip install -r requirements.txt && python facedesk_app.py