I've exported Classfied_Tile formatted image chips from ArcGIS Pro to train a Unet Classifier. However, when setting up 'prepare_data' function I get an UnboundLocalError. I'm running this in Jupyter Lab
Input:
data = prepare_data(data_path, {1:'Ocean', 2:'Sand', 3:'Mud', 4:'Pond', 5:'Red Pond', 6:'Foam', 7:'Tundra', 8:'Bare', 9:'Mud' }, batch_size=16, dataset_type = 'Classified_Tiles')
Output:
---------------------------------------------------------------------------UnboundLocalError Traceback (most recent call last)<ipython-input-9-ab7c0384d6f5> in <module>() 5 # however, this notebook leaves out the fact that you need to directly infer that to the script with 'dataset_type' 6 ----> 7 data = prepare_data(data_path, {1:'Ocean', 2:'Sand', 3:'Mud', 4:'Pond', 5:'Red Pond', 6:'Foam', 7:'Tundra', 8:'Bare', 9:'Mud' }, batch_size=16, dataset_type = 'Classified_Tiles')~\AppData\Local\ESRI\conda\envs\palm-detection\lib\site-packages\arcgis\learn\_data.py in prepare_data(path, class_mapping, chip_size, val_split_pct, batch_size, transforms, collate_fn, seed, dataset_type, resize_to, **kwargs) 463 elif dataset_type == 'Classified_Tiles': 464 --> 465 def get_y_func(x, ext=right): 466 return x.parents[1] / 'labels' / (x.stem + '.{}'.format(ext)) 467 UnboundLocalError: local variable 'right' referenced before assignmentI should mention, I don't get this error when using PASCAL rectangles for SSO training. Looks like it has something to do with classified tiles format.
Can someone help me get around this?
Thanks.
