Dynamic Face Detection Model

Overview

This repository contains a fork of an existing face detection model that has been enhanced to be more dynamic, automatic, and user-friendly. The improvements focus on optimizing the face detection process, allowing for more flexibility and convenience for developers and users alike.

Key Features

• Automatic Face Detection: The model can automatically detect faces without requiring manual configuration.
• Dynamic Model Adaptation: The model adjusts its parameters based on the environment, improving detection accuracy across various conditions.
• Improved Performance: Optimized for faster processing with minimal resource usage.
• Simple Integration: Easily integrable with existing applications or projects.

Installation

Requirements

• Python 3.7+
• TensorFlow (or other dependencies, depending on the base model used)
• OpenCV (for image processing)
• NumPy (for matrix operations)

Setup

1. Clone the repository:

   git clone https://github.com/IceBear3147/FaceDetection

2. Navigate to the project directory:

   cd FaceDetection

3. Install the necessary dependencies:

   pip install -r requirements.txt

4. (Optional) If you plan to use GPU acceleration, install the required GPU-specific dependencies (CUDA, cuDNN).