<jupyter_start><jupyter_text>Apply a trained land classifier model in ArcGIS Pro This tutorial will assume that you have already provisioned a [Geo AI Data Science Virtual Machine](http://aka.ms/dsvm/GeoAI) and are using this Jupyter notebook while connected via remote desktop on that VM. If not, please see our guide to [provisioning and connecting to a Geo AI DSVM](https://github.com/Azure/pixel_level_land_classification/blob/master/geoaidsvm/setup.md).By default, this tutorial will make use of a model we have pre-trained for 250 epochs. If you have completed the associated notebook on [training a land classifier from scratch](./02_Train_a_land_classification_model_from_scratch.ipynb), you will have the option of using your own model file.  Setup instructions Log into ArcGIS Pro[ArcGIS Pro](https://pro.arcgis.com) 2.1.1 is pre-installed on the Geo AI DSVM. If you are running this tutorial on another machine, you may need to perform these additional steps: install ArcGIS Pro, [install CNTK](https://docs.microsoft.com/cognitive-toolkit/setup-windows-python) in the Python environment ArcGIS Pro creates, and ensure that [ArcGIS Pro's Python environment](http://pro.arcgis.com/en/pro-app/arcpy/get-started/installing-python-for-arcgis-pro.htm) is on your system path.To log into ArcGIS Pro, follow these steps:1. Search for and launch the ArcGIS Pro program.1. When prompted, enter your username and password.    - If you don't have an ArcGIS Pro license, see the instructions for getting a trial license in the [intro notebook](./01_Intro_to_pixel-level_land_classification.ipynb).  Install the supporting filesIf you have not already completed the associated notebook on [training a land classifier from scratch](./02_Train_a_land_classification_model_from_scratch.ipynb), execute the following cell to download supporting files to your Geo AI DSVM's D: drive.<jupyter_code>!AzCopy /Source:https://aiforearthcollateral.blob.core.windows.net/imagesegmentationtutorial /SourceSAS:"?st=2018-01-16T10%3A40%3A00Z&se=2028-01-17T10%3A40%3A00Z&sp=rl&sv=2017-04-17&sr=c&sig=KeEzmTaFvVo2ptu2GZQqv5mJ8saaPpeNRNPoasRS0RE%3D" /Dest:D:\pixellevellandclassification /S
print('Done.')<jupyter_output><empty_output>
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