I am using the Deep Learning tools in Python of ArcGIS. I am using the .classify_features() tool. This tool will update the polygon Feature Layer I have on my ArcGIS Online account. It is supposed to make a prediction of either "Damage" or "No Damage" as well as calculate a confidence for each row in the table. This tool however, will only make a prediction and calculate a confidence for the first row only. I plan on using this method on other polygons feature layers in the future so I need to understand why it only calculate for the first row.
My Code Snippet:
#Locations of chips (images and labels) td = r'E:\Thesis_Data\DATA\Maps\Building_Damage_Assessment\Training_Data' #Find published feature layer item = gis.content.search(query="Building Footprints", item_type="Feature Layer Collection") # classify_features (Inferencing) model.classify_features(item.layers, td, 'FID', 'prediction', 'confidence')
I have attached the resultant table as an image.