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## Next steps
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Follow the [Build a classifier](getting-started-build-a-classifier.md) guide to get started using Custom Vision on the web, or complete an [Image classification tutorial](csharp-tutorial.md) to implement a basic scenario in code.
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Follow the [Build a classifier](getting-started-build-a-classifier.md) guide to get started using Custom Vision on the web, or complete an [Image classification tutorial](quickstarts/image-classification.md) to implement a basic scenario in code.
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## Clean up resources
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If you wish to implement your own image classification project (or try an [object detection](../csharp-tutorial-od.md) project instead), you may want to delete the tree identification project from this example. A free trial allows for two Custom Vision projects.
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If you wish to implement your own image classification project (or try an [object detection](../quickstarts/object-detection.md) project instead), you may want to delete the tree identification project from this example. A free trial allows for two Custom Vision projects.
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On the [Custom Vision website](https://customvision.ai), navigate to **Projects** and select the trash can under My New Project.
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## Clean up resources
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If you wish to implement your own object detection project (or try an [image classification](../csharp-tutorial.md) project instead), you may want to delete the fork/scissors detection project from this example. A free trial allows for two Custom Vision projects.
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If you wish to implement your own object detection project (or try an [image classification](../quickstarts/image-classification.md) project instead), you may want to delete the fork/scissors detection project from this example. A free trial allows for two Custom Vision projects.
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On the [Custom Vision website](https://customvision.ai), navigate to **Projects** and select the trash can under My New Project.
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---
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title: "Quickstart: Create an object detection project with the SDK for C# - Custom Vision"
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titleSuffix: Azure Cognitive Services
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description: Create a project, add tags, upload images, train your project, and detect objects using the .NET SDK with C#.
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services: cognitive-services
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author: PatrickFarley
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manager: nitinme
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ms.author: pafarley
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ms.service: cognitive-services
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ms.subservice: custom-vision
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ms.topic: quickstart
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ms.date: 04/14/2020
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ms.author: pafarley
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---
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# Quickstart: Create an object detection project with the Custom Vision .NET SDK
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This article shows you how to get started using the Custom Vision SDK with C# to build an object detection model. After it's created, you can add tagged regions, upload images, train the project, obtain the project's default prediction endpoint URL, and use the endpoint to programmatically test an image. Use this example as a template for building your own .NET application.
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## Prerequisites
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- Any edition of [Visual Studio 2015 or 2017](https://www.visualstudio.com/downloads/)
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This Visual Studio project creates a new Custom Vision project named __My New Project__, which can be accessed through the [Custom Vision website](https://customvision.ai/). It then uploads images to train and test an object detection model. In this project, the model is trained to detect forks and scissors in images.
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[!INCLUDE [get-keys](includes/get-keys.md)]
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[!INCLUDE [get-keys](../../includes/get-keys.md)]
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## Understand the code
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### Create a new Custom Vision Service project
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This next bit of code creates an object detection project. The created project will show up on the [Custom Vision website](https://customvision.ai/) that you visited earlier. See the [CreateProject](https://docs.microsoft.com/dotnet/api/microsoft.azure.cognitiveservices.vision.customvision.training.customvisiontrainingclientextensions.createproject?view=azure-dotnet#Microsoft_Azure_CognitiveServices_Vision_CustomVision_Training_CustomVisionTrainingClientExtensions_CreateProject_Microsoft_Azure_CognitiveServices_Vision_CustomVision_Training_ICustomVisionTrainingClient_System_String_System_String_System_Nullable_System_Guid__System_String_System_Collections_Generic_IList_System_String__) method to specify other options when you create your project (explained in the [Build a detector](get-started-build-detector.md) web portal guide).
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This next bit of code creates an object detection project. The created project will show up on the [Custom Vision website](https://customvision.ai/) that you visited earlier. See the [CreateProject](https://docs.microsoft.com/dotnet/api/microsoft.azure.cognitiveservices.vision.customvision.training.customvisiontrainingclientextensions.createproject?view=azure-dotnet#Microsoft_Azure_CognitiveServices_Vision_CustomVision_Training_CustomVisionTrainingClientExtensions_CreateProject_Microsoft_Azure_CognitiveServices_Vision_CustomVision_Training_ICustomVisionTrainingClient_System_String_System_String_System_Nullable_System_Guid__System_String_System_Collections_Generic_IList_System_String__) method to specify other options when you create your project (explained in the [Build a detector](../../get-started-build-detector.md) web portal guide).
You can then verify that the test image (found in **Images/Test/**) is tagged appropriately and that the region of detection is correct. At this point, you can press any key to exit the application.
Now you've seen how to do every step of the object detection process in code. This sample executes a single training iteration, but often you'll need to train and test your model multiple times in order to make it more accurate. The following guide deals with image classification, but its principles are similar to object detection.
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> [!div class="nextstepaction"]
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> [Test and retrain a model](test-your-model.md)
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> [Test and retrain a model](../../test-your-model.md)
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title: "Quickstart: Create an image classification project with the Custom Vision SDK for C#"
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titleSuffix: Azure Cognitive Services
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description: Create a project, add tags, upload images, train your project, and make a prediction using the .NET SDK with C#.
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services: cognitive-services
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author: PatrickFarley
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manager: nitinme
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ms.author: pafarley
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ms.service: cognitive-services
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ms.subservice: custom-vision
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ms.topic: quickstart
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ms.date: 04/14/2020
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# Quickstart: Create an image classification project with the Custom Vision .NET SDK
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This article provides information and sample code to help you get started using the Custom Vision SDK with C# to build an image classification model. After it's created, you can add tags, upload images, train the project, obtain the project's default prediction endpoint URL, and use the endpoint to programmatically test an image. Use this example as a template for building your own .NET application. If you want to go through the process of building and using a classification model _without_ code, see the [browser-based guidance](getting-started-build-a-classifier.md) instead.
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This article provides information and sample code to help you get started using the Custom Vision SDK with C# to build an image classification model. After it's created, you can add tags, upload images, train the project, obtain the project's default prediction endpoint URL, and use the endpoint to programmatically test an image. Use this example as a template for building your own .NET application. If you want to go through the process of building and using a classification model _without_ code, see the [browser-based guidance](../../getting-started-build-a-classifier.md) instead.
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## Prerequisites
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- Any edition of [Visual Studio 2015 or 2017](https://www.visualstudio.com/downloads/)
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This Visual Studio project creates a new Custom Vision project named __My New Project__, which can be accessed through the [Custom Vision website](https://customvision.ai/). It then uploads images to train and test a classifier. In this project, the classifier is intended to determine whether a tree is a __Hemlock__ or a __Japanese Cherry__.
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[!INCLUDE [get-keys](includes/get-keys.md)]
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[!INCLUDE [get-keys](../../includes/get-keys.md)]
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## Understand the code
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### Create a new Custom Vision service project
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The created project will show up on the [Custom Vision website](https://customvision.ai/) that you visited earlier. See the [CreateProject](https://docs.microsoft.com/dotnet/api/microsoft.azure.cognitiveservices.vision.customvision.training.customvisiontrainingclientextensions.createproject?view=azure-dotnet#Microsoft_Azure_CognitiveServices_Vision_CustomVision_Training_CustomVisionTrainingClientExtensions_CreateProject_Microsoft_Azure_CognitiveServices_Vision_CustomVision_Training_ICustomVisionTrainingClient_System_String_System_String_System_Nullable_System_Guid__System_String_System_Collections_Generic_IList_System_String__) method to specify other options when you create your project (explained in the [Build a classifier](getting-started-build-a-classifier.md) web portal guide).
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The created project will show up on the [Custom Vision website](https://customvision.ai/) that you visited earlier. See the [CreateProject](https://docs.microsoft.com/dotnet/api/microsoft.azure.cognitiveservices.vision.customvision.training.customvisiontrainingclientextensions.createproject?view=azure-dotnet#Microsoft_Azure_CognitiveServices_Vision_CustomVision_Training_CustomVisionTrainingClientExtensions_CreateProject_Microsoft_Azure_CognitiveServices_Vision_CustomVision_Training_ICustomVisionTrainingClient_System_String_System_String_System_Nullable_System_Guid__System_String_System_Collections_Generic_IList_System_String__) method to specify other options when you create your project (explained in the [Build a classifier](../../getting-started-build-a-classifier.md) web portal guide).
You can then verify that the test image (found in **Images/Test/**) is tagged appropriately. Press any key to exit the application. You can also go back to the [Custom Vision website](https://customvision.ai) and see the current state of your newly created project.
Now you've seen how to do every step of the image classification process in code. This sample executes a single training iteration, but often you will need to train and test your model multiple times in order to make it more accurate.
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> [Test and retrain a model](test-your-model.md)
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> [Test and retrain a model](../../test-your-model.md)
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title: "Quickstart: Create an object detection project with the SDK for Go - Custom Vision"
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titleSuffix: Azure Cognitive Services
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description: Create a project, add tags, upload images, train your project, and detect objects using the Go SDK.
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author: areddish
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# Quickstart: Create an object detection project with the Custom Vision Go SDK
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This article provides information and sample code to help you get started using the Custom Vision SDK with Go to build an object detection model. After it's created, you can add tagged regions, upload images, train the project, obtain the project's published prediction endpoint URL, and use the endpoint to programmatically test an image. Use this example as a template for building your own Go application.
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Add the following code to your script to create a new Custom Vision service project. Insert your subscription keys in the appropriate definitions. Also, get your Endpoint URL from the Settings page of the Custom Vision website.
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See the [CreateProject](https://docs.microsoft.com/java/api/com.microsoft.azure.cognitiveservices.vision.customvision.training.trainings.createproject?view=azure-java-stable#com_microsoft_azure_cognitiveservices_vision_customvision_training_Trainings_createProject_String_CreateProjectOptionalParameter_) method to specify other options when you create your project (explained in the [Build a detector](get-started-build-detector.md) web portal guide).
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See the [CreateProject](https://docs.microsoft.com/java/api/com.microsoft.azure.cognitiveservices.vision.customvision.training.trainings.createproject?view=azure-java-stable#com_microsoft_azure_cognitiveservices_vision_customvision_training_Trainings_createProject_String_CreateProjectOptionalParameter_) method to specify other options when you create your project (explained in the [Build a detector](../../get-started-build-detector.md) web portal guide).
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```go
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import(
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The output of the application should appear in the console. You can then verify that the test image (found in **samples/vision/images/Test**) is tagged appropriately and that the region of detection is correct.
Now you've seen how every step of the object detection process can be done in code. This sample executes a single training iteration, but often you'll need to train and test your model multiple times in order to make it more accurate. The following training guide deals with image classification, but its principles are similar to object detection.
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> [Test and retrain a model](test-your-model.md)
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> [Test and retrain a model](../../test-your-model.md)
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