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Copy file name to clipboardExpand all lines: articles/ai-services/computer-vision/how-to/identity-access-token.md
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@@ -112,61 +112,51 @@ curl -X POST 'https://<client-endpoint>/face/v1.0/identify' \
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#### [C#](#tab/csharp)
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The following code snippets show you how to use an access token with the [Face SDK for C#](https://www.nuget.org/packages/Microsoft.Azure.CognitiveServices.Vision.Face).
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The following code snippets show you how to use an access token with the [Face SDK for C#](https://aka.ms/azsdk-csharp-face-pkg).
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The following class uses an access token to create a **ServiceClientCredentials** object that can be used to authenticate a Face API client object. It automatically adds the access token as a header in every request that the Face client will make.
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The following class uses an access token to create a **HttpPipelineSynchronousPolicy** object that can be used to authenticate a Face API client object. It automatically adds the access token as a header in every request that the Face client will make.
Copy file name to clipboardExpand all lines: articles/ai-services/computer-vision/how-to/specify-detection-model.md
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The Face service can extract face data from an image and associate it with a **Person** object through the [Add Person Group Person Face] API. In this API call, you can specify the detection model in the same way as in [Detect].
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See the following code example for the .NET client library.
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See the following .NET code example.
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```csharp
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// Create a PersonGroup and add a person with face detected by "detection_03" model
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## Add face to FaceList with specified model
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You can also specify a detection model when you add a face to an existing **FaceList** object. See the following code example for the .NET client library.
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You can also specify a detection model when you add a face to an existing **FaceList** object. See the following .NET code example.
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```csharp
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using (varcontent=newByteArrayContent(Encoding.UTF8.GetBytes(JsonConvert.SerializeObject(newDictionary<string, object> { ["name"] ="My face collection", ["recognitionModel"] ="recognition_04" }))))
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