media

Image
Embeddings
Converter

Convert images into dense vector representations using state-of-the-art vision models. Embeddings capture semantic visual features and can be used for similarity search, clustering, and cross-modal retrieval.

Max file size: 50 MB

Estimated: 1-3 sec per image

5 input formats

How It Works

Upload an image or provide a URL.

The image is resized and normalized for the selected model.

The vision encoder produces a dense embedding vector.

The vector is returned as a float array with model metadata.

Optionally, the embedding is stored directly in your Mixpeek namespace.

Code Examples

from mixpeek import Mixpeek

client = Mixpeek(api_key="YOUR_API_KEY")

result = client.convert(
    source="https://example.com/product.jpg",
    from_format="image",
    to_format="embeddings",
    options={
        "model": "clip-vit-l-14"
    }
)

print(f"Dimensions: {len(result.embedding)}")

Use Cases

Build visual similarity search for e-commerce catalogs

Detect near-duplicate images across content libraries

Power reverse image search functionality

Enable text-to-image retrieval using shared embedding spaces

Supported Input Formats

JPEG

PNG

WebP

TIFF

BMP

Quick Info

Categorymedia

Max File Size50 MB

Est. Time1-3 sec per image

Extractorimage-descriptor

Try This Conversion

Get started with the Mixpeek API and convert your first file in minutes.

Frequently Asked Questions

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