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Merge pull request #3748 from PatrickFarley/comvis-updates
delete redirect article
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articles/ai-services/.openpublishing.redirection.ai-services.json

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"redirect_url": "/azure/ai-services/computer-vision/",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/ai-services/computer-vision/spatial-analysis-logging.md",
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"redirect_url": "/azure/ai-services/computer-vision/spatial-analysis-container",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/ai-services/document-intelligence/concept-document-intelligence-studio.md",
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"redirect_url": "/azure/ai-services/document-intelligence/studio-overview",

articles/ai-services/computer-vision/index.yml

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- itemType: concept
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text: Camera placement
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url: spatial-analysis-camera-placement.md
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- itemType: concept
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text: Logging and troubleshooting
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url: spatial-analysis-logging.md
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footerLink:
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text: More
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url: intro-to-spatial-analysis-public-preview.md

articles/ai-services/computer-vision/spatial-analysis-camera-placement.md

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<!--* [Deploy a People Counting web application](spatial-analysis-web-app.md)-->
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* [Configure Spatial Analysis operations](./spatial-analysis-operations.md)
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* [Logging and troubleshooting](spatial-analysis-logging.md)
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* [Zone and line placement guide](spatial-analysis-zone-line-placement.md)

articles/ai-services/computer-vision/spatial-analysis-container.md

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When the Edge compute role is set up on the Edge device, it creates two devices: an IoT device and an IoT Edge device. Both devices can be viewed in the IoT Hub resource. The Azure IoT Edge Runtime will already be running on the IoT Edge device.
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> [!NOTE]
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> * Currently only the Linux platform is supported for IoT Edge devices. For help troubleshooting the Azure Stack Edge device, see the [logging and troubleshooting](spatial-analysis-logging.md) article.
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> * Currently only the Linux platform is supported for IoT Edge devices.
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> * To learn more about how to configure an IoT Edge device to communicate through a proxy server, see [Configure an IoT Edge device to communicate through a proxy server](/azure/iot-edge/how-to-configure-proxy-support#azure-portal)
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### Enable MPS on Azure Stack Edge
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## Enable NVIDIA MPS on the host computer
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> [!TIP]
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> * Don't install MPS if your GPU compute capability is less than 7.x (pre Volta). See [CUDA Compatability](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#support-title) for reference.
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> * Don't install MPS if your GPU compute capability is less than 7.x (pre Volta). See [CUDA Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#support-title) for reference.
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> * Run the MPS instructions from a terminal window on the host computer. Not inside your Docker container instance.
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For best performance and utilization, configure the host computer's GPU(s) for [NVIDIA Multiprocess Service (MPS)](https://docs.nvidia.com/deploy/pdf/CUDA_Multi_Process_Service_Overview.pdf). Run the MPS instructions from a terminal window on the host computer.
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## Troubleshooting
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If you encounter issues when starting or running the container, see [Telemetry and troubleshooting](spatial-analysis-logging.md) for steps for common issues. This article also contains information on generating and collecting logs and collecting system health.
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[!INCLUDE [Diagnostic container](../containers/includes/diagnostics-container.md)]
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## Billing
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<!--* [Deploy a People Counting web application](spatial-analysis-web-app.md)-->
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* [Configure Spatial Analysis operations](spatial-analysis-operations.md)
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* [Logging and troubleshooting](spatial-analysis-logging.md)
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* [Camera placement guide](spatial-analysis-camera-placement.md)
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* [Zone and line placement guide](spatial-analysis-zone-line-placement.md)

articles/ai-services/computer-vision/spatial-analysis-local.md

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<!--* [Deploy a People Counting web application](spatial-analysis-web-app.md)-->
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* [Configure Spatial Analysis operations](spatial-analysis-operations.md)
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* [Logging and troubleshooting](spatial-analysis-logging.md)
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* [Camera placement guide](spatial-analysis-camera-placement.md)
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* [Zone and line placement guide](spatial-analysis-zone-line-placement.md)

articles/ai-services/computer-vision/spatial-analysis-logging.md

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articles/ai-services/computer-vision/spatial-analysis-operations.md

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## Next steps
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<!--* [Deploy a People Counting web application](spatial-analysis-web-app.md)-->
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* [Logging and troubleshooting](spatial-analysis-logging.md)
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* [Camera placement guide](spatial-analysis-camera-placement.md)
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* [Zone and line placement guide](spatial-analysis-zone-line-placement.md)

articles/ai-services/computer-vision/spatial-analysis-zone-line-placement.md

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<!--* [Deploy a People Counting web application](spatial-analysis-web-app.md)-->
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* [Configure Spatial Analysis operations](./spatial-analysis-operations.md)
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* [Logging and troubleshooting](spatial-analysis-logging.md)
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* [Camera placement guide](spatial-analysis-camera-placement.md)

articles/ai-services/computer-vision/toc.yml

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href: spatial-analysis-local.md
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#- name: Deploy a people counting web app
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# href: Spatial-analysis-web-app.md
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- name: Logging and troubleshooting
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href: spatial-analysis-logging.md
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- name: Zone and line placement
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href: spatial-analysis-zone-line-placement.md
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- name: Camera placement

articles/ai-services/computer-vision/vehicle-analysis.md

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## Prerequisites
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* To utilize the operations of vehicle analysis, you must first follow the steps to [install and run spatial analysis container](./spatial-analysis-container.md) including configuring your host machine, downloading and configuring your [DeploymentManifest.json](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/ComputerVision/spatial-analysis/DeploymentManifest.json) file, executing the deployment, and setting up device [logging](spatial-analysis-logging.md).
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* To utilize the operations of vehicle analysis, you must first follow the steps to [install and run spatial analysis container](./spatial-analysis-container.md) including configuring your host machine, downloading and configuring your [DeploymentManifest.json](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/ComputerVision/spatial-analysis/DeploymentManifest.json) file, executing the deployment, and setting up device logging.
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* When you configure your [DeploymentManifest.json](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/ComputerVision/spatial-analysis/DeploymentManifest.json) file, refer to the steps below to add the graph configurations for vehicle analysis to your manifest prior to deploying the container. Or, once the spatial analysis container is up and running, you may add the graph configurations and follow the steps to redeploy. The steps below will outline how to properly configure your container.
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* If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/?WT.mc_id=A261C142F) before you begin.
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