Ricerca della somiglianza dei video
Alimentare il sistema di ricerca per similarità dei video con il database vettoriale Zilliz Cloud (completamente gestito da Milvus)
Video Similarity Search With Zilliz Cloud Vector Database
Discover videos resembling your video query with Zilliz Cloud-powered video search engines, proven beneficial for video surveillance, deduplication, recommendation, and beyond.
High-Performant Video 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.
Efficiently Managing Your Spiking Video Search 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.
Real-Time Responses 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 video search systems, guaranteeing uninterrupted service reliability, even in unexpected events through multiple replicas, component isolation, and robust backup and sync capabilities.
Simple Start, Amplified Productivity
Deploy a large-scale 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 per similarità dei video
Un sistema di ricerca per similarità video alimentato da Zilliz funziona nei seguenti modi:
- I video vengono trasformati in embeddings vettoriali utilizzando un modello di embedding.
- Gli embeddings dei video vengono ingeriti e archiviati in Zilliz Cloud.
- Un utente cerca video simili al suo.
- La query video 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 ricerche ANN e recupera i Top-K risultati più rilevanti.
- Zilliz Cloud restituisce i risultati Top-K all'utente.
Storie di Successo
I leader del settore in tutto il mondo utilizzano Milvus o Zilliz Cloud (il Milvus completamente gestito) per alimentare la loro attività di ricerca video.
> 100M
embedding vector storage and searching
Seamlessly integration
with various internal systems and tech stacks
Enhanced real-time data retrieval
with reduced latency and increased system availability
How Milvus Transformed BIGO's Video Deduplication System for Optimal Throughput and User Experience
Leggi ora<200ms
search response time with a high recall rate
>700 million
embedding vectors indexing and management
Significantly increased
query throughput without compromising performance
> 100M
embedding vector storage and searching
Seamlessly integration
with various internal systems and tech stacks
Enhanced real-time data retrieval
with reduced latency and increased system availability
How Milvus Transformed BIGO's Video Deduplication System for Optimal Throughput and User Experience
Leggi ora<200ms
search response time with a high recall rate
>700 million
embedding vectors indexing and management
Significantly increased
query throughput without compromising performance