videoRet retirement warning

Author: PatrickFarley

articles/ai-services/computer-vision/concept-image-retrieval.md

@@ -61,12 +61,12 @@ The following are the main steps of the image retrieval process using Multimodal
 
 ### Relevance score 
 
-The image and video retrieval services return a field called "relevance." The term "relevance" denotes a measure of similarity between a query and image or video frame embeddings. The relevance score is composed of two parts:
-1. The cosine similarity (that falls in the range of [0,1]) between the query and image or video frame embeddings.
-1. A metadata score, which reflects the similarity between the query and the metadata associated with the image or video frame.
+The image retrieval service returns a field called "relevance." The term "relevance" denotes a measure of similarity between a query and image embeddings. The relevance score is composed of two parts:
+1. The cosine similarity (that falls in the range of [0,1]) between the query and image embeddings.
+1. A metadata score, which reflects the similarity between the query and the metadata associated with the image.
 
 > [!IMPORTANT]
-> The relevance score is a good measure to rank results such as images or video frames with respect to a single query. However, the relevance score cannot be accurately compared across queries. Therefore, it's not possible to easily map the relevance score to a confidence level. It's also not possible to trivially create a threshold algorithm to eliminate irrelevant results based solely on the relevance score. 
+> The relevance score is a good measure to rank results such as images with respect to a single query. However, the relevance score cannot be accurately compared across queries. Therefore, it's not possible to easily map the relevance score to a confidence level. It's also not possible to trivially create a threshold algorithm to eliminate irrelevant results based solely on the relevance score. 
 
 ## Input requirements
 

articles/ai-services/computer-vision/includes/video-retrieval-deprecation.md

@@ -11,8 +11,8 @@ ms.update-cycle: 365-days
 ms.author: pafarley
 ---
 
-> [!IMPORTANT]
-> On 30 June 2025, Azure AI Vision Video Retrieval will be retired. The decision to retire this feature is part of our ongoing effort to improve and simplify and improve the features offered for video processing. Migrate to Azure AI Content Understanding and Azure AI Search to benefit from their additional capabilities.
+> [!CAUTION]
+> On 30 June 2025, Azure AI Vision Video Retrieval was retired. The decision to retire this feature was part of our ongoing effort to improve and simplify and improve the features offered for video processing. Migrate to Azure AI Content Understanding and Azure AI Search to benefit from their additional capabilities.
 >
 > **Video processing: Video Retrieval vs Azure AI Content Understanding**
 >
@@ -39,6 +39,3 @@ Video Length Supported|Optimized for short videos, up to ~3 minutes|Supports sho
 |Customization|None|Content Understanding analyzer can be customized to focus using the fields and field descriptions|
 >
 > To start building the search use case with Content Understanding, we recommend starting with this [sample](https://aka.ms/Content-Understanding-Video-Search) which shows how to use Azure AI Search to search videos.
->
-> To avoid service disruptions, migrate by 30 June 2025.
-

articles/ai-services/computer-vision/overview.md

@@ -26,7 +26,6 @@ The Azure AI Vision service gives you access to advanced algorithms that process
 | [Optical Character Recognition (OCR)](overview-ocr.md)|The Optical Character Recognition (OCR) service extracts text from images. You can use the Read API to extract printed and handwritten text from photos and documents. It uses deep-learning-based models and works with text on various surfaces and backgrounds. These include business documents, invoices, receipts, posters, business cards, letters, and whiteboards. The OCR APIs support extracting printed text in [several languages](./language-support.md). Follow the [OCR quickstart](quickstarts-sdk/client-library.md) to get started.|
 |[Image Analysis](overview-image-analysis.md)| The Image Analysis service extracts many visual features from images, such as objects, faces, adult content, and auto-generated text descriptions. Follow the [Image Analysis quickstart](quickstarts-sdk/image-analysis-client-library-40.md) to get started.|
 | [Face](overview-identity.md) | The Face service provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software is important in many different scenarios, such as identification, touchless access control, and face blurring for privacy. Follow the [Face quickstart](quickstarts-sdk/identity-client-library.md) to get started. |
-| [Video Retrieval](intro-to-spatial-analysis-public-preview.md)| Video Retrieval lets you create an index of videos that you can search with natural language. Follow the [how-to guide](/azure/ai-services/computer-vision/how-to/video-retrieval).|
 
 ## Azure AI Vision for digital asset management