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AI Visual Search Engine | AI In Action

ChallengesAI Visual Search Engine

OfficialIntermediateAI Image & Design

5-7 hours

AI Visual Search Engine

Build a visual search application where users upload an image and the system finds visually similar images from a dataset. Implement image embeddings, vector similarity search, and a results interface with relevance scoring.

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embeddingscomputer-visionvisual-searchvector-database

Objectives

Generate image embeddings using a vision model like CLIP
Store embeddings in a vector database for efficient similarity search
Accept image uploads or URLs as search queries
Display ranked results with similarity scores and visual previews
Support filtering results by category or metadata tags

Hints

OpenAI CLIP or Hugging Face models generate excellent image embeddings
Pinecone, Weaviate, or pgvector are good choices for vector storage
Pre-index a dataset of images to have searchable content ready

Resources

huggingface.co/openai/clip-vit-base-patch32
docs.pinecone.io/docs/overview

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