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I'm trying to export a dataset to a dataframe. I'm using the boilerplate code from the example notebook labelpandas-export.ipynb.

The code I"m running is:

df = client.export_to_table( project=project_id, include_performance=True, include_agreement=True, include_metadata=True, mask_method="png", verbose=True )

Here's the error:

Exporting labels from Labelbox for project with ID clr7vo5oc0be6072qacc5cwp0
Export complete: 5 labels exported
Flattening labels...

KeyError Traceback (most recent call last)
in <cell line: 1>()
----> 1 df = client.export_to_table(
2 project=project_id,
3 include_performance=True,
4 include_agreement=True,
5 include_metadata=True,

2 frames
/usr/local/lib/python3.10/dist-packages/labelbase/annotate.py in flatten_label(client, label_dict, ontology_index, datarow_id, mask_method, divider)
390 annotation_value = [array, [255,255,255]]
391 else:
--> 392 png = mask_to_bytes(client=client, input=obj['mask']["url"], datarow_id=datarow_id, method="url", color=[255,255,255], output="png")
393 annotation_value = [png, "null"]
394 if "classifications" in obj.keys():

KeyError: 'mask'

Thanks!

KeyError Traceback (most recent call last)
Cell In[8], line 1
----> 1 df = client.export_to_table(project=project_id)

File ~/opt/anaconda3/envs/research/lib/python3.10/site-packages/labelpandas/client.py:46, in Client.export_to_table(self, project, include_metadata, include_performance, include_agreement, verbose, mask_method, divider)
29 def export_to_table(
30 self, project,
31 include_metadata:bool=False, include_performance:bool=False, include_agreement:bool=False,
32 verbose:bool=False, mask_method:str="png", divider="///"):
33 """ Creates a Pandas DataFrame given a Labelbox Projet ID
34 Args:
35 project : Required (str / lablebox.Project) - Labelbox Project ID or lablebox.Project object to export labels from
(...)
44 divider : Optional (str) - String delimiter for schema name keys and suffix added to duplocate global keys
45 """
---> 46 flattened_labels_dict = export_and_flatten_labels(
47 client=self.lb_client, project=project,
48 include_metadata=include_metadata, include_performance=include_performance, include_agreement=include_agreement,
49 mask_method=mask_method, verbose=verbose, divider=divider
50 )
52 table = pd.DataFrame.from_dict(flattened_labels_dict)
54 if verbose:

File ~/opt/anaconda3/envs/research/lib/python3.10/site-packages/labelbase/downloader.py:59, in export_and_flatten_labels(client, project, include_metadata, include_performance, include_agreement, verbose, mask_method, divider)
51 if not label['Skipped']:
52 flat_label = {
53 "global_key" : label["Global Key"],
54 "row_data" : label["Labeled Data"],
(...)
57 "external_id" : label["External ID"]
58 }
---> 59 res = flatten_label(label_dict=label, ontology_index=ontology_index, schema_to_name_path=schema_to_name_path, mask_method=mask_method, divider=divider)
60 for key, val in res.items():
61 flat_label[f"annotation{divider}{str(key)}"] = val

File ~/opt/anaconda3/envs/research/lib/python3.10/site-packages/labelbase/annotate.py:117, in flatten_label(label_dict, ontology_index, schema_to_name_path, mask_method, divider)
115 annotation_value = [array, [255,255,255]]
116 else:
--> 117 png = mask_to_bytes(input=obj["instanceURI"], method="url", color=[255,255,255], output="png")
118 annotation_value = [png, "null"]
119 if "classifications" in obj.keys():

KeyError: 'instanceURI'