fix naming bugs

Author: Matt Sokoloff

labelbox/data/serialization/labelbox_v1/converter.py

@@ -8,7 +8,7 @@
 from google.api_core import retry
 
 from .label import LBV1Label
-from ...annotation_types.collection import (LabelContainer, LabelGenerator,
+from ...annotation_types.collection import (LabelCollection, LabelGenerator,
                                             PrefetchGenerator)
 
 logger = logging.getLogger(__name__)
@@ -53,12 +53,12 @@ def label_generator():
 
     @staticmethod
     def serialize(
-            labels: LabelContainer) -> Generator[Dict[str, Any], None, None]:
+            labels: LabelCollection) -> Generator[Dict[str, Any], None, None]:
         """
         Converts a labelbox common object to the labelbox json export format
 
         Args:
-            labels: Either a LabelCollection or a LabelGenerator
+            labels: Either a LabelList or a LabelGenerator (LabelCollection)
         Returns:
             A generator for accessing the labelbox json export representation of the data
         """

labelbox/data/serialization/labelbox_v1/label.py

@@ -169,8 +169,8 @@ def from_common(cls, label: Label):
         if label.data.url is None:
             raise ValueError(
                 "Url attribute required for serializing data objects. "
-                "Use <LabelCollection,LabelGenerator>.add_url_to_data "
-                "or <LabelCollection,LabelGenerator>.add_to_dataset")
+                "Use <LabelList,LabelGenerator>.add_url_to_data "
+                "or <LabelList,LabelGenerator>.add_to_dataset")
 
         return LBV1Label(label=label_,
                          data_row_id=label.data.uid,

labelbox/data/serialization/ndjson/classification.py

@@ -189,10 +189,6 @@ def from_common(
             raise TypeError(
                 f"Unable to convert object to MAL format. `{type(annotation.value)}`"
             )
-        if len(annotation.classifications):
-            raise ValueError(
-                "Nested classifications not supported by this format")
-
         return classify_obj.from_common(annotation.value, annotation.schema_id,
                                         annotation.extra, data)
 

labelbox/data/serialization/ndjson/converter.py

@@ -1,7 +1,7 @@
 import logging
 from typing import Any, Dict, Generator, Iterable
 
-from ...annotation_types.collection import LabelContainer, LabelGenerator
+from ...annotation_types.collection import LabelCollection, LabelGenerator
 from .label import NDLabel
 
 logger = logging.getLogger(__name__)
@@ -24,7 +24,7 @@ def deserialize(json_data: Iterable[Dict[str, Any]]) -> LabelGenerator:
 
     @staticmethod
     def serialize(
-            labels: LabelContainer) -> Generator[Dict[str, Any], None, None]:
+            labels: LabelCollection) -> Generator[Dict[str, Any], None, None]:
         """
         Converts a labelbox common object to the labelbox ndjson format (prediction import format)
 
@@ -33,7 +33,7 @@ def serialize(
         We will continue to improve the error messages and add helper functions to deal with this.
 
         Args:
-            labels: Either a LabelCollection or a LabelGenerator
+            labels: Either a LabelList or a LabelGenerator
         Returns:
             A generator for accessing the ndjson representation of the data
         """

labelbox/data/serialization/ndjson/label.py

@@ -6,7 +6,7 @@
 from pydantic import BaseModel
 
 from ...annotation_types.annotation import ClassificationAnnotation, ObjectAnnotation, VideoClassificationAnnotation
-from ...annotation_types.collection import LabelContainer, LabelGenerator
+from ...annotation_types.collection import LabelCollection, LabelGenerator
 from ...annotation_types.data import RasterData, TextData, VideoData
 from ...annotation_types.label import Label
 from ...annotation_types.ner import TextEntity
@@ -26,7 +26,7 @@ def to_common(self) -> LabelGenerator:
 
     @classmethod
     def from_common(cls,
-                    data: LabelContainer) -> Generator["NDLabel", None, None]:
+                    data: LabelCollection) -> Generator["NDLabel", None, None]:
         for label in data:
             yield from cls._create_non_video_annotations(label)
             yield from cls._create_video_annotations(label)

tests/data/serialization/ndjson/test_classification.py

@@ -7,6 +7,6 @@ def test_classification():
     with open('tests/data/assets/ndjson/classification_import.json',
               'r') as file:
         data = json.load(file)
-    res = NDJsonConverter.deserialize(data).as_collection()
+    res = NDJsonConverter.deserialize(data).as_list()
     res = list(NDJsonConverter.serialize(res))
     assert res == data

tests/data/serialization/ndjson/test_image.py

@@ -20,7 +20,7 @@ def test_image():
     with open('tests/data/assets/ndjson/image_import.json', 'r') as file:
         data = json.load(file)
 
-    res = NDJsonConverter.deserialize(data).as_collection()
+    res = NDJsonConverter.deserialize(data).as_list()
     res = list(NDJsonConverter.serialize(res))
     for r in res:
         r.pop('classifications', None)

tests/data/serialization/ndjson/test_nested.py

@@ -6,6 +6,6 @@
 def test_nested():
     with open('tests/data/assets/ndjson/nested_import.json', 'r') as file:
         data = json.load(file)
-    res = NDJsonConverter.deserialize(data).as_collection()
+    res = NDJsonConverter.deserialize(data).as_list()
     res = list(NDJsonConverter.serialize(res))
     assert res == data

tests/data/serialization/ndjson/test_text.py

@@ -6,6 +6,6 @@
 def test_text():
     with open('tests/data/assets/ndjson/text_import.json', 'r') as file:
         data = json.load(file)
-    res = NDJsonConverter.deserialize(data).as_collection()
+    res = NDJsonConverter.deserialize(data).as_list()
     res = list(NDJsonConverter.serialize(res))
     assert res == data

tests/data/serialization/ndjson/test_video.py

@@ -7,6 +7,6 @@ def test_video():
     with open('tests/data/assets/ndjson/video_import.json', 'r') as file:
         data = json.load(file)
 
-    res = NDJsonConverter.deserialize(data).as_collection()
+    res = NDJsonConverter.deserialize(data).as_list()
     res = list(NDJsonConverter.serialize(res))
     assert res == [data[2], data[0], data[1]]