Metadata-Version: 2.4
Name: evoBioMat
Version: 1.0.0
Summary: Enterprise-grade face biometric SDK
Home-page: https://github.com/dakshdubey/evoBioMat_SDK
Author: Daksha Dubey
Author-email: evofu1007@gmail.com
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: opencv-python
Requires-Dist: face-recognition
Requires-Dist: numpy
Requires-Dist: pymysql
Requires-Dist: cryptography
Dynamic: license-file

# EvoBioMat — Enterprise-Grade Face Biometric Python SDK

**EvoBioMat** is a secure, privacy-first, enterprise-grade Python SDK for face biometrics. It allows developers to implement Face ID registration and verification with minimal code, backed by secure encryption and generic database support.

## Features

- **Enterprise-Ready**: Designed for reliability and scale.
- **Secure & Privacy-First**: AES-256 encryption for all biometric data. No raw images are ever stored.
- **Offline-Capable**: Works without internet access for core biometric operations.
- **Deterministic**: Consistent encoding generation.
- **Auditable**: Clear codebase and explicit error handling.

## Installation

### Enterprise / Production Requirements
For production environments (Windows Server, Linux), you must have C++ build tools installed to compile the high-performance biometric engine (`dlib`).

**Windows Setup:**
Run the included setup script as Administrator:
```bash
setup_enterprise_env.bat
```
Or manually install:
- **CMake**: `pip install cmake`
- **Visual Studio Build Tools**: Select "Desktop development with C++".

### Standard Installation
Once dependencies are ready:
```bash
pip install evoBioMat
```

## Quick Start

### Prerequisites
- Python 3.10+
- MySQL Database
- Webcam (for capture)

### Usage

```python
from evobiomat import EvoBioMat
import os

# Configuration (Use environment variables in production)
db_config = {
    "host": "localhost",
    "user": "root",
    "password": "password",
    "database": "biometrics_db"
}

# The encryption key should be a base64url-encoded 32-byte key.
# You can generate one using: cryptography.fernet.Fernet.generate_key()
enc_key = os.environ.get("EVOBIOMAT_KEY", "YOUR_SECURE_KEY_HERE")

# Initialize SDK
bio = EvoBioMat(db_config=db_config, encryption_key=enc_key)

# 1. Register a User
print("Look at the camera for registration...")
try:
    if bio.register("user_123"):
        print("Registration successful!")
except Exception as e:
    print(f"Registration failed: {e}")

# 2. Verify a User
print("Look at the camera for verification...")
result = bio.verify()

if result.is_verified:
    print(f"Access Granted: {result.user_id}")
else:
    print("Face Not Recognized")
```

## Security

EvoBioMat uses AES-256 (via `cryptography` library primitives or Fernet/GCM) to encrypt face encodings at rest. Keys must be managed securely by the implementing application.

## License

MIT
