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RSK World
face-recognition
RSK World
face-recognition
Face Recognition Dataset - Face Recognition + Face Verification + Biometric Authentication + Computer Vision
face-recognition
  • __pycache__
  • data
  • images
  • models
  • scripts
  • .gitignore657 B
  • FEATURES.md5.9 KB
  • GITHUB_RELEASE_INSTRUCTIONS.md5.1 KB
  • INDEX.md4.5 KB
  • INSTALLATION_GUIDE.md3.4 KB
  • ISSUES_FIXED.md2.7 KB
  • LICENSE1.3 KB
  • PROJECT_INFO.txt3.5 KB
  • PROJECT_SUMMARY.md5.7 KB
  • QUICKSTART.md2.1 KB
  • README.md5 KB
  • RELEASE_NOTES.md5.4 KB
  • advanced_demo.py9.1 KB
  • check_errors.py5 KB
  • config.py1.5 KB
  • create_sample_data.py3.8 KB
  • demo.py5.7 KB
  • example_usage.py5 KB
  • index.html41.2 KB
  • project_metadata.json1.4 KB
  • requirements.txt440 B
  • setup_dataset.py2 KB
  • test_system.py10.1 KB
  • train_model.py2.1 KB
QUICKSTART.md
QUICKSTART.md
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QUICKSTART.md

# Quick Start Guide

<!--
Project Information:
- Project ID: 22
- Title: Face Recognition Dataset
- Category: Image Data
- Technologies: PNG, JPG, NumPy, OpenCV, Face Recognition

Contact Information:
RSK World
Founder: Molla Samser
Designer & Tester: Rima Khatun
Email: help@rskworld.in
Phone: +91 93305 39277
Address: Nutanhat, Mongolkote, Purba Burdwan, West Bengal, India, 713147
Website: https://rskworld.in/
Year: 2026
-->

## Installation

1. **Install Python dependencies:**
```bash
pip install -r requirements.txt
```

2. **Set up directory structure:**
```bash
python setup_dataset.py
```

## Dataset Organization

Organize your images in the following structure:

```
data/
train/
person_001/
image1.jpg
image2.jpg
...
person_002/
image1.jpg
image2.jpg
...
```

## Basic Usage

### 1. Train the Model

```bash
python train_model.py
```

### 2. Run Examples

```bash
python example_usage.py
```

### 3. Interactive Demo

```bash
python demo.py
```

## Python API

### Load Dataset

```python
from scripts.load_dataset import FaceDatasetLoader

loader = FaceDatasetLoader('data/train')
images, labels, label_mapping = loader.load()
```

### Preprocess Images

```python
from scripts.preprocess import preprocess_faces

processed_images, processed_labels = preprocess_faces('data/train')
```

### Train and Recognize

```python
from scripts.recognize_faces import FaceRecognizer

# Train
recognizer = FaceRecognizer()
recognizer.train('data/train', save_model=True)

# Recognize
results = recognizer.recognize('path/to/image.jpg')
for result in results:
print(f"Name: {result['name']}, Confidence: {result['confidence']:.2%}")
```

## Features

- Multiple identities support
- Various poses handling
- Different lighting conditions
- Facial landmarks detection
- Ready for face recognition models

## Support

For questions or support, contact:
- Email: help@rskworld.in
- Website: https://rskworld.in/

© 2026 RSK World. All rights reserved.

About RSK World

Founded by Molla Samser, with Designer & Tester Rima Khatun, RSK World is your one-stop destination for free programming resources, source code, and development tools.

Founder: Molla Samser
Designer & Tester: Rima Khatun

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Contact Info

Nutanhat, Mongolkote
Purba Burdwan, West Bengal
India, 713147

+91 93305 39277

hello@rskworld.in
support@rskworld.in

© 2026 RSK World. All rights reserved.

Content used for educational purposes only. View Disclaimer