AL-000: Made confidece optional

Author: dubininsergey

labelbox/data/serialization/ndjson/objects.py

@@ -60,12 +60,12 @@ def from_common(cls,
             'x': point.x,
             'y': point.y
         },
-                   dataRow=DataRow(id=data.uid),
-                   name=name,
-                   schema_id=feature_schema_id,
-                   uuid=extra.get('uuid'),
-                   classifications=classifications,
-                   confidence=confidence)
+            dataRow=DataRow(id=data.uid),
+            name=name,
+            schema_id=feature_schema_id,
+            uuid=extra.get('uuid'),
+            classifications=classifications,
+            confidence=confidence)
 
 
 class NDFramePoint(VideoSupported):
@@ -97,17 +97,18 @@ def from_common(cls, line: Line,
                     classifications: List[ClassificationAnnotation], name: str,
                     feature_schema_id: Cuid, extra: Dict[str, Any],
                     data: Union[ImageData,
-                                TextData], confidence: float) -> "NDLine":
+                                TextData],
+                    confidence: Optional[float] = None) -> "NDLine":
         return cls(line=[{
             'x': pt.x,
             'y': pt.y
         } for pt in line.points],
-                   dataRow=DataRow(id=data.uid),
-                   name=name,
-                   schema_id=feature_schema_id,
-                   uuid=extra.get('uuid'),
-                   classifications=classifications,
-                   confidence=confidence)
+            dataRow=DataRow(id=data.uid),
+            name=name,
+            schema_id=feature_schema_id,
+            uuid=extra.get('uuid'),
+            classifications=classifications,
+            confidence=confidence)
 
 
 class NDFrameLine(VideoSupported):
@@ -151,12 +152,12 @@ def from_common(cls,
             'x': pt.x,
             'y': pt.y
         } for pt in polygon.points],
-                   dataRow=DataRow(id=data.uid),
-                   name=name,
-                   schema_id=feature_schema_id,
-                   uuid=extra.get('uuid'),
-                   classifications=classifications,
-                   confidence=confidence)
+            dataRow=DataRow(id=data.uid),
+            name=name,
+            schema_id=feature_schema_id,
+            uuid=extra.get('uuid'),
+            classifications=classifications,
+            confidence=confidence)
 
 
 class NDRectangle(NDBaseObject, ConfidenceMixin):
@@ -320,7 +321,8 @@ def from_common(cls,
                     confidence: Optional[float] = None) -> "NDMask":
 
         if mask.mask.url is not None:
-            lbv1_mask = _URIMask(instanceURI=mask.mask.url, colorRGB=mask.color)
+            lbv1_mask = _URIMask(
+                instanceURI=mask.mask.url, colorRGB=mask.color)
         else:
             binary = np.all(mask.mask.value == mask.color, axis=-1)
             im_bytes = BytesIO()
@@ -358,12 +360,12 @@ def from_common(cls, text_entity: TextEntity,
             start=text_entity.start,
             end=text_entity.end,
         ),
-                   dataRow=DataRow(id=data.uid),
-                   name=name,
-                   schema_id=feature_schema_id,
-                   uuid=extra.get('uuid'),
-                   classifications=classifications,
-                   confidence=confidence)
+            dataRow=DataRow(id=data.uid),
+            name=name,
+            schema_id=feature_schema_id,
+            uuid=extra.get('uuid'),
+            classifications=classifications,
+            confidence=confidence)
 
 
 class NDObject:

tests/data/assets/ndjson/polyline_without_confidence_import.json

@@ -0,0 +1,25 @@
+[
+    {
+        "line": [
+            {
+                "x": 2534.353,
+                "y": 249.471
+            },
+            {
+                "x": 2429.492,
+                "y": 182.092
+            },
+            {
+                "x": 2294.322,
+                "y": 221.962
+            }
+        ],
+        "uuid": "5ad9c52f-058d-49c8-a749-3f20b84f8cd4",
+        "dataRow": {
+            "id": "cl6xnv9h61fv0085yhtoq06ht"
+        },
+        "name": "some-line",
+        "schemaId": "cl6xnuwt95lqq07330tbb3mfd",
+        "classifications": []
+    }
+]

tests/data/assets/ndjson/text_entity_import.json

@@ -8,7 +8,7 @@
         "dataRow": {
             "id": "cl6xnv9h61fv0085yhtoq06ht"
         },
-        "name": "some-text-emtity",
+        "name": "some-text-entity",
         "schemaId": "cl6xnuwt95lqq07330tbb3mfd",
         "classifications": [],
         "confidence": 0.53

tests/data/assets/ndjson/text_entity_without_confidence_import.json

@@ -0,0 +1,15 @@
+[
+    {
+        "location": {
+            "start": 67,
+            "end": 128
+        },
+        "uuid": "5ad9c52f-058d-49c8-a749-3f20b84f8cd4",
+        "dataRow": {
+            "id": "cl6xnv9h61fv0085yhtoq06ht"
+        },
+        "name": "some-text-entity",
+        "schemaId": "cl6xnuwt95lqq07330tbb3mfd",
+        "classifications": []
+    }
+]

tests/data/serialization/ndjson/test_polyline.py

@@ -1,10 +1,14 @@
 import json
-
+import pytest
 from labelbox.data.serialization.ndjson.converter import NDJsonConverter
 
 
-def test_polyline_import():
-    with open('tests/data/assets/ndjson/polyline_import.json', 'r') as file:
+@pytest.mark.parametrize("filename", [
+    "tests/data/assets/ndjson/polyline_without_confidence_import.json",
+    "tests/data/assets/ndjson/polyline_import.json"
+])
+def test_polyline_import(filename: str):
+    with open(filename, 'r') as file:
         data = json.load(file)
     res = NDJsonConverter.deserialize(data).as_list()
     res = list(NDJsonConverter.serialize(res))

tests/data/serialization/ndjson/test_text_entity.py

@@ -1,9 +1,15 @@
 import json
 
+import pytest
+
 from labelbox.data.serialization.ndjson.converter import NDJsonConverter
 
 
-def test_text_entity_import():
+@pytest.mark.parametrize("filename", [
+    "tests/data/assets/ndjson/text_entity_import.json",
+    "tests/data/assets/ndjson/text_entity_without_confidence_import.json"
+])
+def test_text_entity_import(filename: str):
     with open('tests/data/assets/ndjson/text_entity_import.json', 'r') as file:
         data = json.load(file)
     res = NDJsonConverter.deserialize(data).as_list()