Face Detection

Overview

This project implements a face detection system using machine learning techniques. The goal is to accurately detect and locate faces in images or video streams. This project can be used as a foundation for building more advanced applications.

Features

• Detect faces in images and video streams
• Support for various image formats
• Modern Web Interface: Drag-and-drop image upload and real-time webcam detection.
• Easy to use and extend

Requirements

To run this project, you need to have Python 3 installed along with the following packages:

• PyTorch
• OpenCV
• Pandas
• NumPy
• Matplotlib
• Other dependencies listed in requirements.txt

Installation

1. Clone the repository:

   git clone https://github.com/bvaleksch/FaceDetection.git
   cd FaceDetection
   pip install -r requirements.txt

Train

python3 ./src/train.py

Web Application

This project includes a modern web application built with FastAPI and Vanilla JS.

Features

• Image Upload: Drag & Drop interface to detect faces in uploaded images.
• Live Video: Real-time face detection using your webcam (via WebSockets).

Run the Web App

1. Activate your virtual environment:

   source ~/python_venvs/Facedetection/bin/activate

2. Start the server:

   uvicorn src.web.app:app --reload --host 0.0.0.0 --port 8000

3. Open your browser at http://localhost:8000.

Test

python3 ./src/test.py