Search Similar Images in a Large Unlabeled Dataset

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How to Find Similar Images in a Large Unlabeled Dataset Using Image similarity or Clustering Techniques powered by machine learning?

A Step-by-Step Guide for Beginners and Experts


Introduction

Let’s say you have 20,000+ images and no categories, labels, or tags. Now imagine trying to find just the cat images hidden in there. Manually? Impossible. But with modern AI tools, you can automate this task in a matter of minutes.

In this guide, we’ll walk you through how to:

  • Turn images into searchable vectors using CLIP (by OpenAI)
  • Find similar images using FAISS (by Meta)
  • Handle datasets with no labels at all
  • Optimize for both beginners and advanced users

Tools & Libraries

We’ll use the following libraries:

ToolPurpose
CLIPTurn images (or text!) into embeddings
FaissPerform fast similarity searches
PIL / OpenCVLoad and preprocess images
NumPyHandle vectors and matrix operations
MatplotlibShow results visually

Install them via pip:


Part 1: Beginner-Friendly Step-by-Step Guide

Step 1: Load and Preprocess Images

Use Python to walk through a directory and load images:


Step 2: Generate Embeddings with CLIP

Now extract all embeddings:


Step 3: Build a FAISS Index


Step 4: Find Similar Images (Query with Cat Example)


Step 5: Display Results


Part 2: For Advanced Users

Speed Up with Batching & GPU

Instead of one-by-one embedding:


Save Embeddings for Future Use


Use Cosine Similarity (Optional)


Cluster Similar Images (Optional)


Bonus: Use Text to Find Images (CLIP Magic)

Want to find images with no example image? Just use a sentence.

You can try:

  • “a mountain landscape”
  • “a person dancing”
  • “a close-up of food”

Conclusion

With just a few lines of Python and powerful open-source tools, you can:

  • Search and group unlabeled images
  • Build visual search systems
  • Enable smart content filtering or discovery

Whether you’re a data scientist, developer, or creative — this method opens up new ways to interact with image data.

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