quick fix to support counting unclear in the SDK (#299)

This is a potential patch for handling unclear results for counting
detectors

---------

Co-authored-by: Auto-format Bot <autoformatbot@groundlight.ai>

Author: brandon-wada

generated/docs/CountingResult.md

@@ -4,7 +4,7 @@
 ## Properties
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
-**count** | **int** |  | 
+**count** | **int, none_type** |  | 
 **confidence** | **float** |  | [optional] 
 **source** | **str** |  | [optional] 
 **greater_than_max** | **bool** |  | [optional] 

generated/groundlight_openapi_client/model/counting_result.py

@@ -104,7 +104,10 @@ def openapi_types():
                 and the value is attribute type.
         """
         return {
-            "count": (int,),  # noqa: E501
+            "count": (
+                int,
+                none_type,
+            ),  # noqa: E501
             "confidence": (float,),  # noqa: E501
             "source": (str,),  # noqa: E501
             "greater_than_max": (bool,),  # noqa: E501
@@ -131,7 +134,7 @@ def _from_openapi_data(cls, count, *args, **kwargs):  # noqa: E501
         """CountingResult - a model defined in OpenAPI
 
         Args:
-            count (int):
+            count (int, none_type):
 
         Keyword Args:
             _check_type (bool): if True, values for parameters in openapi_types
@@ -222,7 +225,7 @@ def __init__(self, count, *args, **kwargs):  # noqa: E501
         """CountingResult - a model defined in OpenAPI
 
         Args:
-            count (int):
+            count (int, none_type):
 
         Keyword Args:
             _check_type (bool): if True, values for parameters in openapi_types

generated/model.py

@@ -1,6 +1,6 @@
 # generated by datamodel-codegen:
 #   filename:  public-api.yaml
-#   timestamp: 2024-12-13T20:10:31+00:00
+#   timestamp: 2024-12-19T17:53:53+00:00
 
 from __future__ import annotations
 
@@ -200,7 +200,7 @@ class BinaryClassificationResult(BaseModel):
 class CountingResult(BaseModel):
     confidence: Optional[confloat(ge=0.0, le=1.0)] = None
     source: Optional[Source] = None
-    count: conint(ge=0)
+    count: Optional[conint(ge=0)] = Field(...)
     greater_than_max: Optional[bool] = None
 
 

spec/public-api.yaml

@@ -1381,6 +1381,7 @@ components:
         count:
           type: integer
           minimum: 0
+          nullable: true
         greater_than_max:
           type: boolean
       required:

src/groundlight/client.py

@@ -527,6 +527,9 @@ def get_image_query(self, id: str) -> ImageQuery:  # pylint: disable=redefined-b
         :return: ImageQuery object containing the query details and results
         """
         obj = self.image_queries_api.get_image_query(id=id, _request_timeout=DEFAULT_REQUEST_TIMEOUT)
+        if obj.result_type == "counting" and getattr(obj.result, "label", None):
+            obj.result.pop("label")
+            obj.result["count"] = None
         iq = ImageQuery.parse_obj(obj.to_dict())
         return self._fixup_image_query(iq)
 

test/unit/test_labels.py

@@ -25,13 +25,20 @@ def test_counting_labels(gl_experimental: ExperimentalApi):
     name = f"Test binary labels{datetime.utcnow()}"
     det = gl_experimental.create_counting_detector(name, "test_query", "test_object_class")
     iq1 = gl_experimental.submit_image_query(det, "test/assets/cat.jpeg")
+
     gl_experimental.add_label(iq1, 0)
     iq1 = gl_experimental.get_image_query(iq1.id)
     assert iq1.result.count == 0
+
     good_label = 5
     gl_experimental.add_label(iq1, good_label)
     iq1 = gl_experimental.get_image_query(iq1.id)
     assert iq1.result.count == good_label
+
+    gl_experimental.add_label(iq1, "UNCLEAR")
+    iq1 = gl_experimental.get_image_query(iq1.id)
+    assert iq1.result.count is None
+
     with pytest.raises(ApiException) as _:
         gl_experimental.add_label(iq1, "MAYBE")
     with pytest.raises(ApiException) as _: