Vector search with images
Vector search is a transformative feature of Elasticsearch and other vector stores that enables a method for performing searches within complex data types such as images. Through this approach, images are converted into vectors that can be indexed, searched, and compared against each other, revolutionizing the way we can retrieve and analyze image data. This inherent characteristic of producing embeddings applies to other media types as well. This section provides an in-depth overview of the vector search process with images, including image vectorization, vector indexing in Elasticsearch, kNN search, vector similarity metrics, and fine-tuning the kNN algorithm.
Image vectorization
The first phase of the vector search process involves transforming the image data into a vector, a process known as image vectorization. Deep learning models, specifically CNNs, are typically employed for this task. CNNs are designed to understand and capture the intricate...