SkillHub

xfyun-face-compare

v1.0.0

Compare two face images and return similarity score using iFlytek Face Recognition API.

Sourced from ClawHub, Authored by Dzy-1026

Installation

Please help me install the skill `xfyun-face-compare` from SkillHub official store. npx skills add Dzy-1026/xfyun-face-compare

👤 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.