Ricerca per somiglianza di immagini
Alimentare il vostro sistema di ricerca per similarità di immagini con Zilliz Cloud (la versione completamente gestita di Milvus)
Image Similarity Search with Zilliz Cloud Vector Database
Discover visually similar images effortlessly with Zilliz Cloud-powered image similarity search engines, proving valuable in various fields like e-commerce and art.
Effortlessly Accommodate Your Spiking Image Data
Say goodbye to data size concerns with Zilliz Cloud. Experience horizontal and independent scaling for computing and storage, aligning with your budget and evolving needs. Manage billions of image vectors within hours with efficient bulk inserts.
High-Performant Image Similarity Search with Unparalleled Precision
Experience a 10x performance boost on Zilliz Cloud with advanced indexing algorithms, ensuring millisecond-level latency. Benefit from unparalleled precision using hybrid vector search with scalar filtering and range search capability.
Real-Time Image Search Results for Optimized User Experience
Zilliz Cloud guarantees consistently up-to-date search results through real-time data insertion, deletion, and seamless data flows, significantly optimizing the user experience.
Always On, Always Reliable
Zilliz Cloud builds resilient image search systems, guaranteeing uninterrupted service reliability even in unexpected events through multiple replicas, component isolation, and robust backup and sync capabilities.
Start with Simplicity and Amplified Productivity
Deploy a large-scale image similarity search service in minutes with user-friendly SDKs in multiple languages and streamlined data operations, ensuring an intuitive user experience.
Come Zilliz Cloud alimenta la ricerca di similarità delle immagini
Un sistema di ricerca per similarità di immagini alimentato da Zilliz funziona nel modo seguente:
- Le immagini vengono trasformate in embeddings vettoriali utilizzando un modello di embedding.
- Gli embeddings delle immagini vengono ingeriti e archiviati in Zilliz Cloud.
- Gli utenti cercano immagini simili alle loro immagini di query.
- L'immagine interrogata viene trasformata in embeddings vettoriali utilizzando un modello di embedding.
- Gli embeddings della query vengono inviati a Zilliz Cloud per una ricerca di similarità.
- Zilliz Cloud esegue una [ricerca approssimata del vicino (ANN)] (https://zilliz.com/glossary/anns) e recupera i primi K risultati più rilevanti confrontando la distanza spaziale tra i vettori della query e dell'immagine.
- Zilliz Cloud restituisce all'utente i Top-K risultati.
Storie di Successo
I leader del settore in tutto il mondo utilizzano Milvus o Zilliz Cloud (il Milvus completamente gestito) per costruire i loro sistemi di ricerca di immagini.
90% reduction
in search latency
Sharp reduction
on $ and time
Easily scale
as business grows
Handled tens of millions of
vector embeddings with fast scaling capability
Achieved millisecond-level
query speed with optimal user experience
Reshaped the future of fashion
with a harmonious fusion of human creativity and machine intelligence
90% reduction
in search latency
Sharp reduction
on $ and time
Easily scale
as business grows
Handled tens of millions of
vector embeddings with fast scaling capability
Achieved millisecond-level
query speed with optimal user experience
Reshaped the future of fashion
with a harmonious fusion of human creativity and machine intelligence