dvcrn 👤 Face Compare
Compare two face images and calculate their similarity score using iFlytek's advanced face recognition technology.
Designed for identity verification, face matching, and security authentication scenarios.
✨ Features
- High-accuracy face comparison
- Base64 image encoding support
- Multiple image format support (jpg, png, bmp)
- Detailed similarity scoring
- One-command execution
🚀 Usage
python {baseDir}/scripts/index.py "<image1_path>" "<image2_path>"
Example:
python {baseDir}/scripts/index.py "/path/to/face1.jpg" "/path/to/face2.jpg"
📋 Input Specification
Image Requirements
- Supported formats: JPG, PNG, BMP
- File size: < 4MB recommended
- Image should contain clear, frontal face
- One face per image for best results
⚠ Constraints
- Both image paths must be valid and accessible
- Images must contain detectable faces
- API credentials must be configured
- Network connection required
🔧 Environment Setup
Required:
- Python available in PATH
- Environment variables configured:
export XF_FACE_APP_ID=your_app_id
export XF_FACE_API_KEY=your_api_key
export XF_FACE_API_SECRET=your_api_secret
Or configure it in ~/.openclaw/openclaw.json:
{
"env": {
"XF_FACE_APP_ID": "your_app_id",
"XF_FACE_API_KEY": "your_api_key",
"XF_FACE_API_SECRET": "your_api_secret"
}
}
📦 Output
Returns JSON response with:
- Similarity score (0-100)
- Comparison result (same person or not)
- Confidence level
- Face detection status
🎯 Target Use Cases
- Identity verification
- Access control systems
- Duplicate account detection
- Photo matching services
- Security authentication
- Attendance systems
🛠 Extensibility
Future enhancements may include:
- Batch face comparison
- Face quality assessment
- Multiple face detection
- Liveness detection integration
- Custom threshold configuration
Built for automation workflows and AI-driven identity verification.