Prodigy-ANN for Image Retrieval via CLIP

2023-10-30 · Source: Explosion · Developer tools and consulting for AI, Machine Learning and NLP - Explosion.ai · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics · Depth: Intermediate, short

Summary

The Prodigy-ANN plugin has introduced a new feature enabling Approximate Nearest Neighbors (ANN) techniques for image retrieval, leveraging CLIP embeddings. This update allows users to efficiently index and query large image datasets using text prompts. The process involves using the "Ann image index" recipe to generate and store multimodal CLIP embeddings for images in a specified folder, creating an "images.index" file. Subsequently, the "Ann image fetch" recipe facilitates querying this index with text, such as "MacBook Pro," to retrieve a subset of relevant images based on cosine distance. A further enhancement, the "Ann image manual" recipe, streamlines the annotation workflow by directly presenting query-filtered images, eliminating the need to manually sift through irrelevant examples. This capability significantly accelerates image annotation tasks by focusing on pertinent content.

Key takeaway

For AI Engineers or Data Scientists managing large image datasets for annotation or retrieval, the Prodigy-ANN plugin's new image features offer a significant efficiency boost. You should integrate this tool to leverage multimodal CLIP embeddings, allowing text-based queries to quickly filter and present only the most relevant images. This approach drastically reduces manual review time, accelerating your data labeling and model training pipelines.

Key insights

Multimodal CLIP embeddings enable efficient image retrieval and annotation by querying image databases with text.

Principles

• CLIP embeddings unify image and text in one space.
• Approximate Nearest Neighbors accelerates large-scale search.
• Text queries can filter visual data effectively.

Method

Index images using "Ann image index" to create an embedding store. Query this store with text via "Ann image fetch" to retrieve relevant subsets, or use "Ann image manual" for direct, filtered annotation.

In practice

• Filter large image datasets for specific content.
• Accelerate image annotation workflows.
• Identify images matching textual descriptions.

Topics

• Prodigy-ANN
• Image Retrieval
• CLIP Embeddings
• Approximate Nearest Neighbors
• Multimodal AI
• Data Annotation

Best for: AI Engineer, Machine Learning Engineer, Data Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Explosion · Developer tools and consulting for AI, Machine Learning and NLP - Explosion.ai.