I'm trying to detect trees for a project from aerial imagery and trying to create a tree detection model that does a close to accurate job (the pretrained tree detection model gets less than half the trees and captures many object that aren't trees). I have set up a small amount of training data (I don't really have time to do much more) and when I train a model with just my training data it does a good job at only identifying trees but misses a lot of them.
Is there a way I could use the pretrained model to finetune the model from the training data I have set up? I tried including the pretrained tree detection model as the advanced option in the "Train Deep Learning Model" tool but I get the following error message:
File "c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Image Analyst Tools.tbx\TrainDeepLearningModel.tool\tool.script.execute.py", line 327, in execute
training_model = getattr(arcgis.learn, model_type)
AttributeError: module 'arcgis.learn' has no attribute 'DeepForest'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Image Analyst Tools.tbx\TrainDeepLearningModel.tool\tool.script.execute.py", line 390, in <module>
execute()
File "c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Image Analyst Tools.tbx\TrainDeepLearningModel.tool\tool.script.execute.py", line 385, in execute
del training_model_object
UnboundLocalError: local variable 'training_model_object' referenced before assignment
Thanks!