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+# What's new in Azure AI Vision? - March 2025 Overview
+
+Costa Rica
+
+[](https://github.com)
+[](https://github.com/)
+[brown9804](https://github.com/brown9804)
+
+Last updated: 2025-03-27
+
+----------
+
+
+List of References (Click to expand)
+
+- [What is Azure AI Vision?](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview)
+- [What is Image Analysis?](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0)
+- [What is the Azure AI Face service?](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview-identity)
+- [What is Video Analysis?](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/intro-to-spatial-analysis-public-preview?tabs=sa)
+- [What is Custom Vision?](https://learn.microsoft.com/en-us/azure/ai-services/Custom-Vision-Service/overview)
+- [What's new in Azure AI Vision](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/whats-new)
+
+
+
+## Services Overview
+
+
+Optical Character Recognition (OCR)
+
+> Extracts text from images. You can use the Read API to extract printed and handwritten text from photos and documents. It is used to recognize and convert texts, helping 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.
+
+- **API Endpoint**: The request to the endpoint should include the image data either as a URL or as binary data in the request body. Endpoint format: `/vision/v3.2/read/analyze`
+- **Input Formats**: JPEG, PNG, BMP, PDF (for multi-page documents)
+- **Output**: JSON with detected text and bounding boxes
+- **Languages Supported**: Multiple languages including English, Spanish, French, German, Chinese, Japanese, and more.
+- **Response Structure**: The JSON response includes an array of `readResults`, each containing:
+ - **Page**: The page number (for multi-page documents).
+ - **Language**: The detected language of the text.
+ - **Angle**: The rotation angle of the text.
+ - **Width and Height**: Dimensions of the image.
+ - **Lines**: An array of detected lines of text, each with:
+ - **BoundingBox**: Coordinates of the text line.
+ - **Text**: The recognized text.
+ - **Words**: An array of words within the line, each with its own bounding box and text.
+- **Error Handling**: The API provides detailed error messages for issues such as unsupported file formats, corrupted images, or exceeding size limits.
+- **Performance**: The OCR service is optimized for speed and accuracy, capable of processing large volumes of images quickly.
+
+> Follow the [OCR quickstart](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/client-library?tabs=windows%2Cvisual-studio&pivots=programming-language-python) to get started.
+
+
+
+
+
+From [OCR official documentation](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview-ocr)
+
+
+Image Analysis
+
+> Extracts many visual features from images, such as objects, faces, adult content detection, and auto-generated tags for identification.
+
+- **API Request**: The request to the endpoint should include the image data either as a URL or as binary data in the request body. Endpoint format: `/vision/v3.2/analyze`
+- **Response Structure**: The JSON response includes an array of `categories`, `tags`, `objects`, `faces`, `color`, and `imageType`, each containing:
+ - **Categories**: Classifies images into predefined categories. An array of categories with `name` and `score` indicating the confidence level.
+ - **Tags**: Identifies objects, living beings, scenery, and actions. An array of tags with `name` and `confidence` score.
+ - **Objects**: Provides coordinates for objects within an image. An array of detected objects with `rectangle` coordinates and `object` name.
+ - **Faces**: Detects faces and provides attributes like age, gender, and emotion. An array of detected faces with `age`, `gender`, `faceRectangle`, and `emotion`.
+ - **Color**: Determines dominant colors. Information about the dominant colors, accent color, and whether the image is black & white.
+ - **ImageType**: Identifies whether an image is a photograph, clipart, or line drawing. Details about the image type, such as whether it is a clipart or line drawing.
+- **Text Extraction (OCR)**: Extracts printed and handwritten text.
+- **Output**: JSON with detected features and their details.
+- **Error Handling**: The API provides detailed error messages for issues such as unsupported file formats, corrupted images, or exceeding size limits.
+- **Performance**: The Image Analysis service is optimized for speed and accuracy, capable of processing large volumes of images quickly.
+
+> Follow the [Image Analysis quickstart](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/image-analysis-client-library-40?tabs=visual-studio%2Cwindows&pivots=programming-language-python) to get started.
+
+
+
+| **Feature** | **Description** | **Use Case** |
+|-------------------------------|---------------------------------------------------------------------------------|-----------------------------------------------------------------------------|
+| **Analyze Image (minus 4.0 Captions)** | Extracts multiple information including:
- Tagging
- Object detection
- OCR (Optical Character Recognition)
- Face detection
- Categorization
- Color analysis
- Image type detection
| Useful for applications requiring comprehensive image analysis without the need for detailed captions. |
+| **Analyze Image (including 4.0 Captions)** | Includes all Analyze Image features plus enhanced image captioning for detailed descriptions. | Ideal for applications needing both comprehensive image analysis and detailed descriptive captions. |
+| **Product Recognition** | Recognizes and provides detailed information about products within images. | Beneficial for e-commerce platforms to identify and catalog products from images. |
+| **Multimodal embeddings** | Combines visual and textual data to improve search, retrieval, and support complex queries. | Enhances search engines by integrating visual content with text-based queries to provide more accurate results. |
+| **Background removal** | Removes backgrounds from images to isolate the main subject for enhanced focus and editing. | Useful in graphic design and photo editing to create cleaner images by isolating subjects from their backgrounds. |
+
+| Generate image captions | Tag visual features | Background removal (v4.0 preview only) |
+| ----- | ----- | ---- |
+|
|
|
|
+
+From [official documentation](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0)
+
+
+Face
+
+> Provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software can be important in many different scenarios such as identifying people in photos or videos or finding a particular individual among a large group of people.
+
+- **API Endpoint**: `/face/v1.0/detect`
+- **API Request**: The request to the endpoint should include the image data either as a URL or as binary data in the request body. The request can also specify which features to analyze using query parameters.
+ - **Parameters**:
+ - `returnFaceId`: Boolean to specify if face IDs should be returned.
+ - `returnFaceLandmarks`: Boolean to specify if face landmarks should be returned.
+ - `returnFaceAttributes`: Comma-separated string to specify which face attributes to return (e.g., `age,gender,emotion`).
+- **Features**:
+ - **Face Detection**: Identifies human faces and provides bounding boxes.
+ - **Face Recognition**: Matches detected faces against a database of known faces.
+ - **Face Verification**: Compares two faces to determine if they belong to the same person.
+ - **Face Grouping**: Groups similar faces together.
+ - **Face Attributes**: Provides detailed attributes like age, gender, emotion, head pose, facial hair, and accessories.
+- **Output**: JSON with detected faces and their attributes.
+- **Response Structure**: The JSON response includes an array of detected faces, each containing:
+ - **FaceId**: Unique identifier for the detected face.
+ - **FaceRectangle**: Coordinates of the bounding box around the face.
+ - **FaceLandmarks**: (Optional) Detailed coordinates of facial landmarks.
+ - **FaceAttributes**: (Optional) Detailed attributes of the face, including:
+ - `age`: Estimated age of the person.
+ - `gender`: Gender of the person.
+ - `emotion`: Detected emotions with confidence scores.
+ - `headPose`: Orientation of the head.
+ - `facialHair`: Presence of facial hair.
+ - `glasses`: Type of glasses worn.
+ - `accessories`: Detected accessories like headwear.
+ - `blur`: Blur level of the image.
+ - `exposure`: Exposure level of the image.
+ - `noise`: Noise level of the image.
+- **Error Handling**: The API provides detailed error messages for issues such as unsupported file formats, corrupted images, or exceeding size limits. Common error codes include:
+ - `InvalidImageFormat`: The provided image format is not supported.
+ - `InvalidImageSize`: The provided image exceeds the size limit.
+ - `FaceNotFound`: No faces were detected in the image.
+- **Performance**: The Face API is optimized for speed and accuracy, capable of processing large volumes of images quickly. It supports high concurrency and provides low-latency responses.
+
+> Follow the [Face quickstart](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/identity-client-library?tabs=windows%2Cvisual-studio&pivots=programming-language-csharp) to get started.
+
+
+
+
+
+From [official documentation](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview-identity)
+
+| **Feature** | **Description** | **Use Case** |
+|-------------------------------|---------------------------------------------------------------------------------|-----------------------------------------------------------------------------|
+| **Face Detection and Recognition** | Detects and identifies faces in images. Provides attributes like age, gender, and emotion. Supports face verification and identification for security purposes. - **Face Detection**: Locates faces within an image.
- **Face Recognition**: Matches detected faces against a database of known faces.
- **Attributes**: Age, gender, emotion, head pose, facial hair, and accessories.
| - Security systems
- Social media applications
- Customer insights
|
+| **Person Identification** | Identifies individuals in images based on a pre-enrolled database. - **Enrollment**: Register faces in a database.
- **Identification**: Match faces in images to enrolled faces.
| - Access control
- Personalized experiences
- Surveillance systems
|
+| **Face Verification** | Compares two faces to determine if they belong to the same person. - **One-to-One Matching**: Verify if two faces are the same.
| - Authentication systems
- Login verification
- Fraud prevention
|
+| **Face Grouping** | Groups similar faces together in a collection of images. - **Clustering**: Automatically group similar faces.
| - Organizing photo libraries
- Social media platforms
|
+| **Face Attributes** | Analyzes facial features to provide detailed attributes, including head pose, facial hair, and accessories. - **Attributes**: Age, gender, emotion, head pose, facial hair, and accessories.
| - Demographic analysis
- Marketing insights
- User profiling
|
+
+
+Video Analysis
+
+> Includes video-related features like [Spatial Analysis](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/spatial-analysis-container?tabs=azure-stack-edge) and [Video Retrieval](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/video-retrieval). Spatial analysis analyzes real-time footage captured by cameras in relation to predefined areas of interest or rules set by users for specific actions or events within a video feed and produces events accordingly when rules are met.
+
+- **API Endpoint**: `/video/v1.0/analyze`
+- **API Request**: The request to the endpoint should include the video data either as a URL or as binary data in the request body. The request can also specify which features to analyze using query parameters.
+ - **Parameters**:
+ - `spatialAnalysis`: Boolean to specify if spatial analysis should be performed.
+ - `peopleCounting`: Boolean to specify if people counting should be performed.
+ - `movementTracking`: Boolean to specify if people movement tracking should be performed.
+ - `zoneMonitoring`: Boolean to specify if zone monitoring should be performed.
+ - `lineCrossingDetection`: Boolean to specify if line crossing detection should be performed.
+ - `customEvents`: Boolean to specify if custom events should be defined and detected.
+- **Features**:
+ - **Spatial Analysis**: Monitors and analyzes movements and interactions within physical spaces.
+ - **People Counting**: Counts the number of people in a designated area.
+ - **People Movement Tracking**: Tracks the movement of individuals within a space.
+ - **Zone Monitoring**: Detects when people enter or exit specific zones.
+ - **Line Crossing Detection**: Detects when people cross predefined lines.
+ - **Custom Events**: Defines custom events based on spatial criteria.
+- **Output**: JSON with detected events and their details.
+- **Response Structure**: The JSON response includes an array of detected events, each containing:
+ - **EventId**: Unique identifier for the detected event.
+ - **EventType**: Type of the detected event (e.g., `PeopleCounting`, `ZoneMonitoring`).
+ - **Timestamp**: Time at which the event was detected.
+ - **Details**: Detailed information about the event, including:
+ - `count`: Number of people detected (for people counting).
+ - `coordinates`: Coordinates of detected movements or zone entries/exits.
+ - `lineCrossed`: Information about the line crossed (for line crossing detection).
+ - `customEventDetails`: Details about custom events defined by the user.
+- **Error Handling**: The API provides detailed error messages for issues such as unsupported file formats, corrupted videos, or exceeding size limits. Common error codes include:
+ - `InvalidVideoFormat`: The provided video format is not supported.
+ - `InvalidVideoSize`: The provided video exceeds the size limit.
+ - `EventNotDetected`: No events were detected in the video.
+- **Performance**: The Video Analysis service is optimized for speed and accuracy, capable of processing large volumes of video data quickly. It supports high concurrency and provides low-latency responses.
+
+
+
+| **Feature** | **Description** | **Use Case** |
+|-------------------------------|---------------------------------------------------------------------------------|-----------------------------------------------------------------------------|
+| **People Counting** | Counts the number of people in a specified area. - **Real-time Counting**: Provides live updates on the number of people.
- **Historical Data**: Tracks changes over time.
| - Retail analytics
- Event management
- Public safety
|
+| **People Movement Tracking** | Tracks the movement of individuals within a specified area. - **Path Tracking**: Monitors the paths taken by individuals.
- **Heatmaps**: Visualizes areas of high activity.
| - Customer behavior analysis
- Facility management
- Security monitoring
|
+| **Zone Monitoring** | Monitors specific zones for activity. - **Zone Entry/Exit**: Detects when individuals enter or exit predefined zones.
- **Activity Monitoring**: Tracks activities within zones.
| - Restricted area monitoring
- Workplace safety
- Compliance enforcement
|
+| **Line Crossing Detection** | Detects when individuals cross a predefined line. - **Boundary Monitoring**: Alerts when boundaries are crossed.
- **Security Applications**: Enhances perimeter security.
| - Perimeter security
- Access control
- Intrusion detection
|
+| **Custom Events** | Allows the creation of custom events based on specific criteria. - **Event Definition**: Define custom events based on movement, count, or zone activity.
- **Alerting**: Set up alerts for custom events.
| - Tailored security solutions
- Custom analytics
- Event-driven applications
|
+
+> E.g People counting:
+
+https://github.com/user-attachments/assets/eb7be305-b61e-45b7-8a3c-4d9378b7d99f
+
+> E.g Social distancing and face mask detection:
+
+https://github.com/user-attachments/assets/cd8f4f18-5cfe-43c6-865e-0480021d699e
+
+From [official documentation](https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/intro-to-spatial-analysis-public-preview?tabs=sa)
+
+## What's new in Azure AI Vision?
+
+| **Update** | **Description** | **Details** |
+|-------------------------------------------------|---------------------------------------------------------------------------------|-----------------------------------------------------------------------------|
+| **Face Liveness Detection GA** | The Face liveness detection feature is now generally available (GA). | - **Release Date**: January 2025
- **Server-side API**: Face API v1.2
- **Client-side SDK**: Azure AI Vision SDK 1.0.0
- **Capabilities**: Allows developers to utilize face liveness checks on both native-mobile applications and web-browser applications for identity-verification scenarios.
- **Modes**: Supports both Passive and Passive-Active modes. The hybrid Passive-Active mode requires Active motion only in poor lighting conditions, while using the speed and efficiency of Passive liveness checks in optimal lighting.
- **More Information**: [See the SDK release notes](https://github.com/Azure-Samples/azure-ai-vision-sdk/releases/tag/1.1.0). |
+| **Face Liveness Client-Side SDK 1.1.0 Release** | Release of the new version of the Face Liveness Client-Side SDK. | - **Release Date**: February 2025
- **Improvements**: - Increased timeout for the head-turn scenario to provide end-users more time to complete the flow.
- Fixes to iOS and Android SDKs to resolve compatibility issues with Microsoft Intune Mobile Application Management SDKs.
- Security related fixes/improvements.
- **More Information**: [See the SDK release notes](https://github.com/Azure-Samples/azure-ai-vision-sdk/releases/tag/1.0.0). |
+| **Image Analysis 4.0 Preview API Deprecation** | Deprecation of the Image Analysis 4.0 Preview API. | - **Deprecation Date**: March 31, 2025
- **Migration**: Users need to migrate their Azure Image Analysis workloads to the Image Analysis 4.0 GA API before the deprecation date.
- **Improvements**: Access to features such as multimodal embedding, synchronous OCR, people detection, image tagging, smart cropping, caption, dense caption, and image object detection.
- **Retired Preview APIs**: - 2022-07-31-preview
- 2022-10-12-preview
- 2023-02-01-preview
- 2023-04-01-preview
- 2023-07-01-preview
- v4.0-preview.1
- **Removed Features**: Model customization, background removal, product recognition (removed from Studio experience as of January 10, 2025).
- **Alternative**: Transition to [Azure AI Custom Vision](https://learn.microsoft.com/en-us/azure/ai-services/Custom-Vision-Service/overview) for similar functionality. |
+
+
+
Total Visitors
+

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