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Val Brodsky
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Update Sphynx to a minimum version required by readthedocs and fix documentation errors
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+28
-19
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4 files changed

+28
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docs/requirements.txt

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@@ -1,2 +1,2 @@
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Sphinx==4.5.0
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Sphinx~=5.3.0
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sphinx-rtd-theme==0.5.1

labelbox/schema/annotation_import.py

Lines changed: 17 additions & 12 deletions
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@@ -51,6 +51,7 @@ def inputs(self) -> List[Dict[str, Any]]:
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def errors(self) -> List[Dict[str, Any]]:
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"""
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Errors for each individual annotation uploaded. This is a subset of statuses
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Returns:
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List of dicts containing error messages. Empty list means there were no errors
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See `AnnotationImport.statuses` for more details.
@@ -63,22 +64,26 @@ def errors(self) -> List[Dict[str, Any]]:
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def statuses(self) -> List[Dict[str, Any]]:
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"""
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Status for each individual annotation uploaded.
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Returns:
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A status for each annotation if the upload is done running.
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See below table for more details
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.. list-table::
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:widths: 15 150
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:header-rows: 1
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* - Field
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- Description
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* - uuid
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- Specifies the annotation for the status row.
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* - dataRow
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- JSON object containing the Labelbox data row ID for the annotation.
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* - status
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- Indicates SUCCESS or FAILURE.
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* - errors
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- An array of error messages included when status is FAILURE. Each error has a name, message and optional (key might not exist) additional_info.
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:widths: 15 150
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:header-rows: 1
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* - Field
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- Description
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* - uuid
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- Specifies the annotation for the status row.
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* - dataRow
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- JSON object containing the Labelbox data row ID for the annotation.
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* - status
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- Indicates SUCCESS or FAILURE.
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* - errors
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- An array of error messages included when status is FAILURE. Each error has a name, message and optional (key might not exist) additional_info.
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* This information will expire after 24 hours.
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"""
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self.wait_until_done()

labelbox/schema/dataset.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -68,10 +68,10 @@ def data_rows(
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"""
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Custom method to paginate data_rows via cursor.
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Params:
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Args:
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from_cursor (str): Cursor (data row id) to start from, if none, will start from the beginning
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where (dict(str,str)): Filter to apply to data rows. Where value is a data row column name and key is the value to filter on.
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example: {'external_id': 'my_external_id'} to get a data row with external_id = 'my_external_id'
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example: {'external_id': 'my_external_id'} to get a data row with external_id = 'my_external_id'
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NOTE:

labelbox/schema/model_run.py

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@@ -57,7 +57,9 @@ def upsert_labels(self,
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label_ids: Optional[List[str]] = None,
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project_id: Optional[str] = None,
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timeout_seconds=3600):
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""" Adds data rows and labels to a Model Run
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"""
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Adds data rows and labels to a Model Run
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Args:
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label_ids (list): label ids to insert
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project_id (string): project uuid, all project labels will be uploaded
@@ -271,14 +273,16 @@ def add_predictions(
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name: str,
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predictions: Union[str, Path, Iterable[Dict], Iterable["Label"]],
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) -> 'MEAPredictionImport': # type: ignore
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""" Uploads predictions to a new Editor project.
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"""
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Uploads predictions to a new Editor project.
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Args:
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name (str): name of the AnnotationImport job
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predictions (str or Path or Iterable):
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url that is publicly accessible by Labelbox containing an
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predictions (str or Path or Iterable): url that is publicly accessible by Labelbox containing an
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ndjson file
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OR local path to an ndjson file
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OR iterable of annotation rows
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Returns:
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AnnotationImport
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"""

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