acrolinx

Author: PatrickFarley

articles/ai-services/computer-vision/how-to/specify-detection-model.md

@@ -1,7 +1,7 @@
 ---
 title: How to specify a detection model - Face
 titleSuffix: Azure AI services
-description: This article will show you how to choose which face detection model to use with your Azure AI Face application.
+description: This article shows you how to choose which face detection model to use with your Azure AI Face application.
 #services: cognitive-services
 author: PatrickFarley
 manager: nitinme
@@ -19,7 +19,7 @@ ms.custom: devx-track-csharp
 
 This guide shows you how to specify a face detection model for the Azure AI Face service.
 
-The Face service uses machine learning models to perform operations on human faces in images. We continue to improve the accuracy of our models based on customer feedback and advances in research, and we deliver these improvements as model updates. Developers have the option to specify which version of the face detection model they'd like to use; they can choose the model that best fits their use case.
+The Face service uses machine learning models to perform operations on human faces in images. We continue to improve the accuracy of our models based on customer feedback and advances in research, and we deliver these improvements as model updates. Developers can specify which version of the face detection model they'd like to use; they can choose the model that best fits their use case.
 
 Read on to learn how to specify the face detection model in certain face operations. The Face service uses face detection whenever it converts an image of a face into some other form of data.
 
@@ -41,7 +41,7 @@ The different face detection models are optimized for different tasks. See the f
 | Model | Description | Performance notes   | Attributes  | Landmarks |
 |---------|------------|-------------------|-------------|--|
 |**detection_01** | Default choice for all face detection operations. | Not optimized for small, side-view, or blurry faces.                                                     | Returns main face attributes (head pose, glasses, and so on) if they're specified in the detect call. | Returns face landmarks if they're specified in the detect call. |
-|**detection_02** | Released in May 2019 and available optionally in all face detection operations.   | Improved accuracy on small, side-view, and blurry faces.  | Does not return face attributes. | Does not return face landmarks.     |
+|**detection_02** | Released in May 2019 and available optionally in all face detection operations.   | Improved accuracy on small, side-view, and blurry faces.  | Doesn't return face attributes. | Doesn't return face landmarks.     |
 |**detection_03** | Released in February 2021 and available optionally in all face detection operations.                   | Further improved accuracy, including on smaller faces (64x64 pixels) and rotated face orientations.       | Returns mask, blur, and head pose attributes if they're specified in the detect call. | Returns face landmarks if they're specified in the detect call. |
 
 
@@ -57,11 +57,11 @@ When you use the [Detect] API, you can assign the model version with the `detect
 * `detection_02`
 * `detection_03`
 
-A request URL for the [Detect] REST API will look like this:
+A request URL for the [Detect] REST API looks like this:
 
 `https://westus.api.cognitive.microsoft.com/face/v1.0/detect[?returnFaceId][&returnFaceLandmarks][&returnFaceAttributes][&recognitionModel][&returnRecognitionModel][&detectionModel]&subscription-key=<Subscription key>`
 
-If you are using the client library, you can assign the value for `detectionModel` by passing in an appropriate string. If you leave it unassigned, the API will use the default model version (`detection_01`). See the following code example for the .NET client library.
+If you are using the client library, you can assign the value for `detectionModel` by passing in an appropriate string. If you leave it unassigned, the API uses the default model version (`detection_01`). See the following code example for the .NET client library.
 
 ```csharp
 string imageUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/Face/images/detection1.jpg";
@@ -85,7 +85,7 @@ string imageUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-ser
 await client.PersonGroupPerson.AddFaceFromUrlAsync(personGroupId, personId, imageUrl, detectionModel: "detection_03");
 ```
 
-This code creates a **PersonGroup** with ID `mypersongroupid` and adds a **Person** to it. Then it adds a Face to this **Person** using the `detection_03` model. If you don't specify the *detectionModel* parameter, the API will use the default model, `detection_01`.
+This code creates a **PersonGroup** with ID `mypersongroupid` and adds a **Person** to it. Then it adds a Face to this **Person** using the `detection_03` model. If you don't specify the *detectionModel* parameter, the API uses the default model, `detection_01`.
 
 > [!NOTE]
 > You don't need to use the same detection model for all faces in a **Person** object, and you don't need to use the same detection model when detecting new faces to compare with a **Person** object (in the [Identify From Person Group] API, for example).
@@ -101,7 +101,7 @@ string imageUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-ser
 await client.FaceList.AddFaceFromUrlAsync(faceListId, imageUrl, detectionModel: "detection_03");
 ```
 
-This code creates a **FaceList** called `My face collection` and adds a Face to it with the `detection_03` model. If you don't specify the *detectionModel* parameter, the API will use the default model, `detection_01`.
+This code creates a **FaceList** called `My face collection` and adds a Face to it with the `detection_03` model. If you don't specify the *detectionModel* parameter, the API uses the default model, `detection_01`.
 
 > [!NOTE]
 > You don't need to use the same detection model for all faces in a **FaceList** object, and you don't need to use the same detection model when detecting new faces to compare with a **FaceList** object.