Local Image Embeddings in .NET | CLIP + ONNX Multimodal AI

In this video we move beyond text embeddings and explore multimodal AI in .NET. We’ll: Understand how CLIP maps images and text into the same vector space Run image embeddings locally using ONNX Runtime Build a simple image search scenario Connect it to a lightweight RAG-style chat Discuss the journey from local experimentation to Azure AI scale Running locally helps you understand embeddings deeply. From there, moving to Azure AI Search or Azure OpenAI becomes a natural next step. 🔗 Resources 📦 Code & Samples Main Repo: https://github.com/elbruno/elbruno.lo... Image Samples: https://github.com/elbruno/elbruno.lo... NuGet Package: https://www.nuget.org/packages/ElBrun... 📚 Model & Technology References OpenAI CLIP research: https://openai.com/research/clip CLIP Paper: https://arxiv.org/abs/2103.00020 Model on Hugging Face: https://huggingface.co/openai/clip-vi... ONNX: https://onnx.ai ONNX Runtime: https://github.com/microsoft/onnxruntime 🚀 Next Experiments Combine text + image embeddings Store vectors in Azure AI Search Compare CLIP vs Azure Vision embeddings Integrate with Microsoft Agent Framework If you're building AI in .NET, my advice will be: Start local - Understand the fundamentals - Scale in Azure ⏱️ Chapters 00:00 Introduction – From Text to Image Embeddings 01:10 Why Multimodal Matters 02:40 What is CLIP? 04:30 What is ONNX & ONNX Runtime? 06:20 Downloading the Model 07:40 Walking Through the Code 10:30 Running Image Search 13:20 RAG Chat Demo 16:00 Language Limitations 18:20 From Local to Azure 20:00 Reflections & Next Steps