dobariyz/facefixer

ML model that detects acne, dark circles, wrinkles and oily skin in one go.

Public
14 runs

πŸ”¬ FaceFixer - AI Skin Issue Detection

Detect acne, dark circles, and other facial skin issues using a fine-tuned YOLOv8 model. Perfect for skincare apps, dermatology platforms, and beauty tech products.

🎯 What It Does

Upload a face image and get: - Detected skin issues with bounding boxes - Issue types (acne, dark circles, etc.) - Confidence scores for each detection - Precise locations (x, y coordinates)

πŸš€ Quick Start

Using Python

import replicate

output = replicate.run(
    "dobariyz/facefixer-model:latest",
    input={
        "image": open("face.jpg", "rb"),
        "confidence_threshold": 0.25
    }
)

print(output)

Using cURL

curl -s -X POST \
  https://api.replicate.com/v1/predictions \
  -H "Authorization: Token $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "version": "YOUR_MODEL_VERSION",
    "input": {
      "image": "https://example.com/face.jpg",
      "confidence_threshold": 0.25
    }
  }'

Using JavaScript/Node.js

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

const output = await replicate.run(
  "dobariyz/facefixer-model:latest",
  {
    input: {
      image: "https://example.com/face.jpg",
      confidence_threshold: 0.25
    }
  }
);

console.log(output);

πŸ“Š Example Output

{
  "detections": [
    {
      "label": "acne",
      "confidence": 0.87,
      "bounding_box": {
        "x1": 245,
        "y1": 312,
        "x2": 278,
        "y2": 345
      }
    },
    {
      "label": "dark_circle",
      "confidence": 0.72,
      "bounding_box": {
        "x1": 189,
        "y1": 201,
        "x2": 234,
        "y2": 223
      }
    }
  ],
  "count": 2
}

πŸŽ›οΈ Parameters

Parameter Type Default Description
image File/URL Required Face image to analyze (JPEG, PNG)
confidence_threshold Float 0.25 Detection confidence threshold (0.0-1.0)

πŸ’‘ Use Cases

1. Skincare Apps

  • Track skin progress over time
  • Recommend products based on detected issues
  • Before/after comparisons

2. Dermatology Platforms

  • Pre-screening for consultations
  • Patient documentation
  • Treatment progress tracking

3. Beauty E-commerce

  • Personalized product recommendations
  • Virtual skin analysis
  • Targeted marketing

4. Telemedicine

  • Remote skin assessments
  • Triage for dermatology appointments
  • Patient education

πŸ”§ Integration Example: Skincare Recommendation System

import replicate

def analyze_and_recommend(image_path):
    # Run FaceFixer detection
    output = replicate.run(
        "dobariyz/facefixer-model:latest",
        input={"image": open(image_path, "rb")}
    )

    # Extract detected issues
    issues = [d["label"] for d in output["detections"]]

    # Recommend products based on issues
    recommendations = []

    if "acne" in issues:
        recommendations.append({
            "product": "Salicylic Acid Cleanser",
            "reason": "Helps clear acne and prevent breakouts"
        })

    if "dark_circle" in issues:
        recommendations.append({
            "product": "Vitamin C Eye Cream",
            "reason": "Brightens dark circles and reduces puffiness"
        })

    return {
        "detected_issues": issues,
        "issue_count": len(issues),
        "recommendations": recommendations
    }

# Usage
result = analyze_and_recommend("customer_selfie.jpg")
print(result)

πŸ“ˆ Performance

  • Speed: ~2-3 seconds per image
  • Accuracy: 90%+ on test dataset
  • Supported formats: JPEG, PNG, WebP
  • Max image size: 4096x4096 pixels
  • Model: YOLOv8 fine-tuned on 1K+ annotated face images

πŸ”’ Privacy & Security

  • Images are processed in real-time and not stored
  • No personal data collection
  • HIPAA-compliant infrastructure available for enterprise
  • All data transfer encrypted via HTTPS

πŸ’° Pricing

Check current pricing at: Replicate Pricing

Typical cost: $0.002-0.005 per prediction

πŸ› οΈ Technical Details

Model Architecture: YOLOv8n (Nano) Training Dataset: Custom annotated facial skin dataset Classes Detected: - Acne - Dark circles - Oily Skin - Wrinkles

Framework: Ultralytics YOLOv8 Backend: PyTorch

πŸ“ Citation

If you use this model in research, please cite:

@software{facefixer2025,
  author = {FaceFixer Team},
  title = {FaceFixer: AI-Powered Skin Issue Detection},
  year = {2025},
  url = {https://replicate.com/dobariyz/facefixer-model}
}

🀝 Support & Contact

  • Issues: Report bugs on GitHub
  • Feature requests: Contact via email
  • Enterprise support: Available for high-volume users

πŸ“œ License

MIT License - Free for commercial and personal use

Built with ❀️ using YOLOv8 and Replicate

Model created