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Image embedding refers to the process of converting an image into a numerical representation, often in the form of a vector or a set of numerical features. The goal of image embedding is to capture the essential information and characteristics of an image in a way that can be easily processed and compared.

The similarity of images can be inferred from their respective embeddings. If two images have similar numerical representations (vectors), it suggests that they share similar visual features. In this context, image embedding is a technique used in image similarity search, content-based image retrieval, and other applications where comparing images based on their content is important. 

SentenceTransformers, as shown in 2384, is a framework for state-of-the-art sentence, text and image embeddings in Python.

Figure 2384. SentenceTransformers.

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