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Help using the land_cover_classification_using_unet jupyter notebook sample

Question asked by rfairhur24 Champion on Jul 24, 2019
Latest reply on Sep 4, 2019 by

I downloaded a set of sample Jupyter notebooks from esri at  One of the notebooks is called land_cover_classification_using_unet, which is supposed to showcase an end-to-end to land cover classification workflow using ArcGIS API for Python. The workflow consists of three major steps: (1) extract training data, (2) train a deep learning image segmentation model, (3) deploy the model for inference and create maps. 


I am having trouble running the notebook, and so far have only gotten the first two steps to work, which just create a connection to ArcGIS Online.  The third and fourth lines of code are supposed to access a labeled image to train the model, but I get an error that the index value is out of range no matter what index value I use, which basically means the image was not found. 


label_layer ="Kent_county_full_label_land_cover")[1] # the index might change
IndexError                                Traceback (most recent call last)
<ipython-input-29-a4ac34d0306c> in <module>
----> 1 label_layer ="Kent_county_full_label_land_cover")[1] # the index might change
      2 label_layer

IndexError: list index out of range


I downloaded the original classified image for Kent County in Deleware from the Chesapeake Conservancy land cover project.  It looks the same, although I am not completely sure it matches the the extent or classifications of the training image the notebook was supposed to use.


How do I change the code to use the image I downloaded and saved on my computer rather than the image from ArcGIS Online?


I will probably will be asking more questions as I progress though the code, since it seems likely I will hit other problems.  I am hoping to first be able to complete the notebook example covering the Deleware region and afterward adapt it to process the NAIP imagery for my jurisdiction.