[[["์ดํดํ๊ธฐ ์ฌ์","easyToUnderstand","thumb-up"],["๋ฌธ์ ๊ฐ ํด๊ฒฐ๋จ","solvedMyProblem","thumb-up"],["๊ธฐํ","otherUp","thumb-up"]],[["์ดํดํ๊ธฐ ์ด๋ ค์","hardToUnderstand","thumb-down"],["์๋ชป๋ ์ ๋ณด ๋๋ ์ํ ์ฝ๋","incorrectInformationOrSampleCode","thumb-down"],["ํ์ํ ์ ๋ณด/์ํ์ด ์์","missingTheInformationSamplesINeed","thumb-down"],["๋ฒ์ญ ๋ฌธ์ ","translationIssue","thumb-down"],["๊ธฐํ","otherDown","thumb-down"]],["์ต์ข ์ ๋ฐ์ดํธ: 2025-09-01(UTC)"],[],[],null,["# Vertex AI Vision overview\n\nVertex AI Vision is an AI-powered platform to ingest, analyze and store video\ndata. Vertex AI Vision lets users build and deploy\napplications with a simplified user interface.\n\nUsing Vertex AI Vision you can build end-to-end computer image solutions by\nleveraging Vertex AI Vision's\nintegration with other major components, namely Live Video Analytics,\ndata streams, and Vision Warehouse. The Vertex AI Vision API allows you to\nbuild a high level app from low level APIs, and create and update a high\nlevel workflow that combines multiple individual API calls. You can then\nexecute your workflow as a unit by making a single deploy request to\nthe Vertex AI Vision platform server.\n\nUsing Vertex AI Vision, you can:\n\n- Ingest real-time video data\n- Analyze data for insights using general and custom vision AI models\n- Store insights in Vision Warehouse for simplified querying and metadata information\n\nVertex AI Vision workflow\n-------------------------\n\nThe steps you complete to use Vertex AI Vision are as follows:\n\n1. **Ingest real-time data**\n\n Vertex AI Vision's architecture allows you to quickly and\n conveniently stream real-time video ingestion infrastructure in a\n public Cloud.\n2. **Analyze data**\n\n After data is ingested, Vertex AI Vision's framework provides you with easy\n access and orchestration of a large and growing portfolio of *general* ,\n *custom* ,\n \\& *specialized* analysis models.\n3. **Store and query output**\n\n After your app analyzes your data you can send this information to a\n storage destination (Vision Warehouse or BigQuery), or\n receive the data live. With Vision Warehouse you can send your app\n output to a warehouse that generalizes your search work and serves\n multiple data types and use cases.\n\n*A graph for a Vertex AI Vision occupancy analytics app in the Google Cloud console*\n\nA note on Responsible AI\n------------------------\n\nAt Google Cloud, we prioritize helping customers safely develop and implement\nsolutions using Vertex AI Vision. For Vertex AI Vision, we've worked to\ndevelop fair and equitable performance in accordance with\n[Google's AI Principles](https://ai.google/principles/).\n\nThis work includes testing for bias during development, for example looking at\nperformance across different skin tones, and developing product features to\nenhance privacy and limit personal identification, like person and face blur.\nWe are committed to iterating and improving, and we will continue to\nincorporate best practices and lessons learned into our Vertex AI\nproducts.\n\nWhen Vertex AI Vision is integrated into a customer's unique organizational\ncontext, there are likely to be additional responsible AI considerations.\nWe encourage customers to leverage fairness, interpretability, privacy and\nsecurity [best practices](https://ai.google/responsibilities/responsible-ai-practices/?category=general) when implementing Vertex AI Vision,\nespecially when building custom or AutoML trained models. Throughout this\ntechnical documentation, we have provided additional guidance and resources to\nsupport this work. To learn more, read about Google's recommendations\nfor [Responsible AI practices](https://ai.google/responsibilities/responsible-ai-practices/?category=general).\n\nWhat's next\n-----------\n\n- Read more in the blog post [\"Vertex AI Vision: Easily build and deploy computer vision\n applications at scale\"](https://cloud.google.com/blog/products/ai-machine-learning/computer-vision-for-vertex-ai).\n- Learn details about specific models in the [Occupancy analytics guide](/vision-ai/docs/occupancy-analytics-model), [Person blur guide](/vision-ai/docs/person-blur-model), [Person/vehicle detector guide](/vision-ai/docs/person-vehicle-model), or [Motion filtering guide](/vision-ai/docs/motion-filtering-model).\n- Try Vertex AI Vision in the Google Cloud console by reading the [Build an app in the console](/vision-ai/docs/build-app-console-quickstart) quickstart.\n- [Set up your local environment](/vision-ai/docs/cloud-environment) to use Vertex AI Vision."]]
