10-of-my-most-popular-text-to-image-series-prompts-78b0897e
generate a bunch of images, then you curate the results to handpick the best ones
Compare two face images and return similarity score using iFlytek Face Recognition API.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
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skillhub install dzy-1026/xfyun-face-compareInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
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.
python {baseDir}/scripts/index.py "<image1_path>" "<image2_path>"
Example:
python {baseDir}/scripts/index.py "/path/to/face1.jpg" "/path/to/face2.jpg"
Required:
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"
}
}
Returns JSON response with:
Future enhancements may include:
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# 👤 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
```bash
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:
```bash
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`:
```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 de...generate a bunch of images, then you curate the results to handpick the best ones
generate a bunch of images, then you curate the results to handpick the best ones
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