# Face-Recognition-with-OpenCV

**Repository Path**: li-tingcong/Face-Recognition-with-OpenCV

## Basic Information

- **Project Name**: Face-Recognition-with-OpenCV
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-05-20
- **Last Updated**: 2025-05-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Face-Recognition-with-OpenCV

- This is a simple Face Recognition project using Python OpenCV, to learn and understand the basics of a project. This project is inspired by https://github.com/leodlca/lbph-face-recognition.
- For Face Detection we use OpenCV's cascade: *haarcascade_frontalface_alt.xml*, which can be found at https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_frontalface_alt.xml.
- We use the Local Binary Pattern Histogram (LBPH) Algorithm for training and recognizing the different faces. LBPH algorithm creates More about the LBPH algorithm at https://towardsdatascience.com/face-recognition-how-lbph-works-90ec258c3d6b

### About the Project

We use the OpenCV library's pre-trained models to perform the task of Face Recognition using the LBPH algorithm.
OpenCV offers several for the task of object Detection. We use the Frontal-Face Haar Cascade to detect a "face" in the frame. Once a face is detected it has a bounded box to find its location, and the face is extracted, leaving aside the other non-important details in the frame.
The LBPH algotihm is then run on the extracted face.

### Requirements

- Python 3.6+
- OpenCV
- Numpy
- Pandas

### Taking Photos
1. Run `python TakePhotos.py`
2. Enter an ID and Name
3. Press the `s` key repeatedly to take photos, once a box appears around your face. It is recommended to take atleast 25 pictures.
4. Press the `q` key when you're finished taking pictures.

### Training the Model
1. Run `python Train.py`
2. After Training is complete the program will generate the file "Classifiers/TrainedLBPH.yml"

### Recognizing
1. Run `python Recognize.py`