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A personalized skincare recommendation system using OpenCV for facial image capture and preprocessing, CNN for skin type classification, and MLP for product selection based on ingredient analytics. Enabled image-based skin assessment and intelligent recommendations via a dual-model pipeline.

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ananyaarramalla/GlowMatch

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✨ GlowMatch!

An AI-powered skincare recommendation system that analyzes your skin using computer vision and deep learning and matches you with the most suitable products based on skin type, concerns, and ingredient compatibility.

  1. 💡 Introduction
  2. ⚙️ Tech Stack
  3. 🛠️ Features
  4. 🖼️ Screenshots
  5. 🚀 Future Enhancements
  • Finding the right skincare products can be overwhelming.
  • GlowMatch! uses AI models + ingredient analysis to provide personalized skincare suggestions, helping users discover products that truly match their needs while avoiding harmful or incompatible ingredients.
  • Machine Learning: CNN, MLP, OpenCV
  • Libraries: NumPy, Pandas, scikit-learn
  • Tools: Jupyter Notebook

✅ AI-powered skin analysis using computer vision

✅ Personalized skincare product recommendations

✅ Ingredient frequency analysis

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  • 📱 Mobile and Web application
  • 🔬 Advanced skin concern detection (acne, pigmentation, dryness)
  • 🧾 Product reviews integration (community-based)
  • 🌐 Multi-language support

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A personalized skincare recommendation system using OpenCV for facial image capture and preprocessing, CNN for skin type classification, and MLP for product selection based on ingredient analytics. Enabled image-based skin assessment and intelligent recommendations via a dual-model pipeline.

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