Fix logic for deriving data types for annotations

Author: Val Brodsky

libs/labelbox/src/labelbox/data/serialization/ndjson/label.py

@@ -156,8 +156,11 @@ def _infer_media_type(
             raise ValueError("Missing annotations while inferring media type")
 
         types = {type(annotation) for annotation in annotations}
+        types_values = {type(annotation.value) for annotation in annotations}
         data = ImageData
-        if (TextEntity in types) or (ConversationEntity in types):
+        if (ObjectAnnotation
+                in types) and ((TextEntity in types_values) or
+                               (ConversationEntity in types_values)):
             data = TextData
         elif VideoClassificationAnnotation in types or VideoObjectAnnotation in types:
             data = VideoData

libs/labelbox/src/labelbox/schema/internal/data_row_upsert_item.py

@@ -7,7 +7,7 @@
 from labelbox.schema.data_row import DataRow
 
 
-class DataRowItemBase(ABC, pydantic_compat.BaseModel):
+class DataRowItemBase(ABC, BaseModel):
     """
     Base class for creating payloads for upsert operations.
     """