Merge remote-tracking branch 'up/main' into engsys/puppeteer-v21

rush.json

@@ -2148,6 +2148,11 @@
       "projectFolder": "sdk/playwrighttesting/arm-playwrighttesting",
       "versionPolicyName": "management"
     },
+    {
+      "packageName": "@azure-rest/ai-vision-image-analysis",
+      "projectFolder": "sdk/vision/ai-vision-image-analysis-rest",
+      "versionPolicyName": "client"
+    },
     {
       "packageName": "@azure/arm-hybridnetwork",
       "projectFolder": "sdk/hybridnetwork/arm-hybridnetwork",

sdk/vision/ai-vision-image-analysis-rest/.eslintrc.json

@@ -0,0 +1,11 @@
+{
+  "plugins": ["@azure/azure-sdk"],
+  "extends": ["plugin:@azure/azure-sdk/azure-sdk-base"],
+  "rules": {
+    "@azure/azure-sdk/ts-modules-only-named": "warn",
+    "@azure/azure-sdk/ts-apiextractor-json-types": "warn",
+    "@azure/azure-sdk/ts-package-json-types": "warn",
+    "@azure/azure-sdk/ts-package-json-engine-is-present": "warn",
+    "tsdoc/syntax": "warn"
+  }
+}

sdk/vision/ai-vision-image-analysis-rest/CHANGELOG.md

@@ -0,0 +1,7 @@
+# Release History
+
+## 1.0.0-beta.1 (2024-01-09)
+
+### Features Added
+Initial release of Image Analysis SDK. Uses the generally available [Computer Vision REST API (2023-10-01)](https://eastus.dev.cognitive.microsoft.com/docs/services/Cognitive_Services_Unified_Vision_API_2023-10-01).
+

sdk/vision/ai-vision-image-analysis-rest/README.md

@@ -0,0 +1,200 @@
+# Azure AI Vision Image Analysis client library for JavaScript
+
+The Image Analysis service provides AI algorithms for processing images and returning information about their content. In a single service call, you can extract one or more visual features from the image simultaneously, including getting a caption for the image, extracting text shown in the image (OCR) and detecting objects. For more information on the service and the supported visual features, see [Image Analysis overview][image_analysis_overview], and the [Concepts][image_analysis_concepts] page.
+
+Use the Image Analysis client library to:
+* Authenticate against the service
+* Set what features you would like to extract
+* Upload an image for analysis, or send an image URL
+* Get the analysis result
+
+[Product documentation][image_analysis_overview] 
+| [Samples](https://github.com/Azure/azure-sdk-for-js/tree/rhurey/ia_dev/sdk/vision/ai-vision-image-analysis-rest/samples)
+| [Vision Studio][vision_studio]
+| [API reference documentation](https://learn.microsoft.com/javascript/api/overview/azure/visual-search)
+
+## Getting started
+
+### Currently supported environments
+
+- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)
+- Latest versions of Safari, Chrome, Edge, and Firefox.
+
+See our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.
+
+### Prerequisites
+
+- An [Azure subscription](https://azure.microsoft.com/free).
+- A [Computer Vision resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesComputerVision) in your Azure subscription.
+  * You will need the key and endpoint from this resource to authenticate against the service.
+  * You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
+  * Note that in order to run Image Analysis with the `Caption` or `Dense Captions` features, the Azure resource needs to be from one of the following GPU-supported regions: `East US`, `France Central`, `Korea Central`, `North Europe`, `Southeast Asia`, `West Europe`, or `West US`.
+
+### Install the `@azure-rest/ai-vision-image-analysis` package
+
+Install the Image Analysis client library for JavaScript with `npm`:
+
+```bash
+npm install @azure-rest/ai-vision-image-analysis
+```
+
+### Browser support
+
+#### JavaScript Bundle
+
+To use this client library in the browser, first, you need to use a bundler. For details on how to do this, please refer to our [bundling documentation](https://aka.ms/AzureSDKBundling).
+
+## Key concepts
+
+Once you've initialized an `ImageAnalysisClient`, you need to select one or more visual features to analyze. The options are specified by the enum class `VisualFeatures`. The following features are supported:
+
+1. `VisualFeatures.Caption`: ([Examples](#analyze-an-image-from-url) | [Samples](https://github.com/Azure/azure-sdk-for-js/tree/rhurey/ia_dev/sdk/vision/ai-vision-image-analysis-rest/samples)) Generate a human-readable sentence that describes the content of an image.
+1. `VisualFeatures.Read`: ([Examples](#extract-text-from-an-image-url) | [Samples](https://github.com/Azure/azure-sdk-for-js/tree/rhurey/ia_dev/sdk/vision/ai-vision-image-analysis-rest/samples)) Also known as Optical Character Recognition (OCR). Extract printed or handwritten text from images.
+1. `VisualFeatures.DenseCaptions`: Dense Captions provides more details by generating one-sentence captions for up to 10 different regions in the image, including one for the whole image.
+1. `VisualFeatures.Tags`: Extract content tags for thousands of recognizable objects, living beings, scenery, and actions that appear in images.
+1. `VisualFeatures.Objects`: Object detection. This is similar to tagging, but focused on detecting physical objects in the image and returning their location.
+1. `VisualFeatures.SmartCrops`: Used to find a representative sub-region of the image for thumbnail generation, with priority given to include faces.
+1. `VisualFeatures.People`: Locate people in the image and return their location.
+
+For more information about these features, see [Image Analysis overview][image_analysis_overview], and the [Concepts][image_analysis_concepts] page.
+
+### Supported image formats
+
+Image Analysis works on images that meet the following requirements:
+
+* The image must be presented in JPEG, PNG, GIF, BMP, WEBP, ICO, TIFF, or MPO format
+* The file size of the image must be less than 20 megabytes (MB)
+* The dimensions of the image must be greater than 50 x 50 pixels and less than 16,000 x 16,000 pixels
+
+### ImageAnalysisClient
+
+The `ImageAnalysisClient` is the primary interface for developers interacting with the Image Analysis service. It serves as the gateway from which all interaction with the library will occur.
+
+## Examples
+
+### Authenticate the client
+
+Here's an example of how to create an `ImageAnalysisClient` instance using a key-based authentication and an Azure Active Directory authentication.
+
+
+```javascript Snippet:ImageAnalysisAuthKey
+const { ImageAnalysisClient, KeyCredential } = require("@azure-rest/ai-image-analysis");
+
+const endpoint = "<your_endpoint>";
+const key = "<your_key>";
+const credential = new KeyCredential(key);
+
+const client = new ImageAnalysisClient(endpoint, credential);
+```
+
+### Analyze an image from URL
+
+The following example demonstrates how to analyze an image using the Image Analysis client library for JavaScript.
+
+```javascript Snippet:ImageAnalysisFromUrl
+const imageUrl = "https://example.com/image.jpg";
+const features = ["Caption", "DenseCaptions", "Objects", "People", "Read", "SmartCrops", "Tags"];
+
+async function analyzeImageFromUrl() {
+  const result = await client.path("/imageanalysis:analyze").post({
+    body: {
+      url: imageUrl,
+    },
+    queryParameters: {
+      features: features,
+      "smartCrops-aspect-ratios": [0.9, 1.33],
+    },
+    contentType: "application/json",
+  });
+
+  console.log("Image analysis result:", result.body);
+}
+
+analyzeImageFromUrl();
+```
+
+### Analyze an image from a local file
+
+In this example, we will analyze an image from a local file using the Image Analysis client library for JavaScript.
+
+```javascript Snippet:ImageAnalysisFromLocalFile
+const fs = require("fs");
+
+const imagePath = "./path/to/your/image.jpg";
+const features = ["Caption", "DenseCaptions", "Objects", "People", "Read", "SmartCrops", "Tags"];
+
+async function analyzeImageFromFile() {
+  const imageBuffer = fs.readFileSync(imagePath);
+
+  const result = await client.path("/imageanalysis:analyze").post({
+    body: imageBuffer,
+    queryParameters: {
+      features: features,
+      "smartCrops-aspect-ratios": [0.9, 1.33],
+    },
+    contentType: "application/octet-stream",
+  });
+
+  console.log("Image analysis result:", result.body);
+}
+
+analyzeImageFromFile();
+```
+
+### Extract text from an image Url
+This example demonstrates how to extract printed or hand-written text for the image file [sample.jpg](https://aka.ms/azai/vision/image-analysis-sample.jpg) using the ImageAnalysisClient. The method call returns an ImageAnalysisResult object. The ReadResult property on the returned object includes a list of text lines and a bounding polygon surrounding each text line. For each line, it also returns a list of words in the text line and a bounding polygon surrounding each word.
+``` javascript Snippet:readmeText
+const client: ImageAnalysisClient = createImageAnalysisClient(endpoint, credential);
+
+const features: string[] = [
+  'Read'
+];
+
+const imageUrl: string = 'https://aka.ms/azai/vision/image-analysis-sample.jpg';
+
+client.path('/imageanalysis:analyze').post({
+  body: { url: imageUrl },
+  queryParameters: { features: features },
+  contentType: 'application/json'
+}).then(result => {
+  const iaResult: ImageAnalysisResultOutput = result.body as ImageAnalysisResultOutput;
+
+  // Process the response
+  if (iaResult.readResult && iaResult.readResult.blocks.length > 0) {
+    iaResult.readResult.blocks.forEach(block => {
+      console.log(`Detected text block: ${JSON.stringify(block)}`);
+    });
+  } else {
+    console.log('No text blocks detected.');
+  }
+```
+
+## Troubleshooting
+
+### Logging
+
+Enabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:
+
+```javascript
+const { setLogLevel } = require("@azure/logger");
+
+setLogLevel("info");
+```
+
+For more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).
+
+## Next steps
+
+Please take a look at the [samples](https://github.com/Azure/azure-sdk-for-js/tree/rhurey/ia_dev/sdk/vision/ai-vision-image-analysis-rest/samples) directory for detailed examples that demonstrate how to use the client libraries.
+
+## Contributing
+
+If you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.
+
+## Related projects
+
+- [Microsoft Azure SDK for JavaScript](https://github.com/Azure/azure-sdk-for-js)
+
+[image_analysis_overview]: https://learn.microsoft.com/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0
+[image_analysis_concepts]: https://learn.microsoft.com/azure/ai-services/computer-vision/concept-tag-images-40
+[vision_studio]: https://portal.vision.cognitive.azure.com/gallery/imageanalysis

sdk/vision/ai-vision-image-analysis-rest/api-extractor.json

@@ -0,0 +1,31 @@
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sdk/vision/ai-vision-image-analysis-rest/assets.json

@@ -0,0 +1,6 @@
+{
+  "AssetsRepo": "Azure/azure-sdk-assets",
+  "AssetsRepoPrefixPath": "js",
+  "TagPrefix": "js/vision/ai-vision-image-analysis-rest",
+  "Tag": "js/vision/ai-vision-image-analysis-rest_19acc08c63"
+}