Deep Face Detection

This repository contains code for deep face detection using OpenCV. It utilizes the LabelMe tool for labeling the dataset and Albumentations library for data augmentation.

Overview

Facial detection is a crucial task in various computer vision applications, including surveillance, human-computer interaction, and biometrics. This project focuses on developing a deep learning-based solution for accurate face detection using the OpenCV library, which provides powerful tools for image processing and computer vision tasks.

Features

• Dataset Labeling: Utilize the LabelMe tool to annotate faces in images. The annotations are saved in XML format, providing bounding box coordinates for each labeled face.
• Data Augmentation: Apply data augmentation techniques using the Albumentations library to enhance the diversity of the dataset. Augmentation helps improve the robustness and generalization of the trained model.
• Training: Train a deep learning model for face detection using the labeled and augmented dataset.

Use Cases

This project can be applied to numerous use cases, including but not limited to:

1. Facial Recognition
2. Facial Expression Recognition

Installation

Provide installation instructions for your project.

# Example:
git clone https://github.com/tkarim45/Deep-Face-Detection.git
cd Deep-CNN-Classifier-with-Any-Images

Prerequisites

You would need the following dependencies to run the code

# Example:
pip install -r requirements.txt

How to Label the data using labelme library

Watch the video

Contribution

Contributions are welcome!