Adding count mode tests

src/groundlight/client.py

@@ -244,6 +244,38 @@ def list_detectors(self, page: int = 1, page_size: int = 10) -> PaginatedDetecto
         )
         return PaginatedDetectorList.parse_obj(obj.to_dict())
 
+    def _prep_create_detector(
+            self,
+            name: str,
+            query: str,
+            *,
+            group_name: Optional[str] = None,
+            confidence_threshold: Optional[float] = None,
+            patience_time: Optional[float] = None,
+            pipeline_config: Optional[str] = None,
+            metadata: Union[dict, str, None] = None,
+    ) -> Detector:
+        """
+        A helper function to prepare the input for creating a detector. Individual create_detector
+        methods may add to the input before calling the API.
+        """
+        detector_creation_input = DetectorCreationInputRequest(
+            name=name,
+            query=query,
+            pipeline_config=pipeline_config,
+        )
+        if group_name is not None:
+            detector_creation_input.group_name = group_name
+        if metadata is not None:
+            detector_creation_input.metadata = str(url_encode_dict(metadata, name="metadata", size_limit_bytes=1024))
+        if confidence_threshold:
+            detector_creation_input.confidence_threshold = confidence_threshold
+        if isinstance(patience_time, int):
+            patience_time = float(patience_time)
+        if patience_time:
+            detector_creation_input.patience_time = patience_time
+        return detector_creation_input
+
     def create_detector(  # noqa: PLR0913
         self,
         name: str,
@@ -279,21 +311,15 @@ def create_detector(  # noqa: PLR0913
         :return: Detector
         """
 
-        detector_creation_input = DetectorCreationInputRequest(
+        detector_creation_input = self._prep_create_detector(
             name=name,
             query=query,
+            group_name=group_name,
+            confidence_threshold=confidence_threshold,
+            patience_time=patience_time,
             pipeline_config=pipeline_config,
+            metadata=metadata,
         )
-        if group_name is not None:
-            detector_creation_input.group_name = group_name
-        if metadata is not None:
-            detector_creation_input.metadata = str(url_encode_dict(metadata, name="metadata", size_limit_bytes=1024))
-        if confidence_threshold:
-            detector_creation_input.confidence_threshold = confidence_threshold
-        if isinstance(patience_time, int):
-            patience_time = float(patience_time)
-        if patience_time:
-            detector_creation_input.patience_time = patience_time
         obj = self.detectors_api.create_detector(detector_creation_input, _request_timeout=DEFAULT_REQUEST_TIMEOUT)
         return Detector.parse_obj(obj.to_dict())
 

src/groundlight/experimental_api.py

@@ -8,7 +8,7 @@
 
 import json
 from io import BufferedReader, BytesIO
-from typing import Any, Dict, List, Tuple, Union
+from typing import Any, Dict, List, Optional, Tuple, Union
 
 import requests
 from groundlight_openapi_client.api.actions_api import ActionsApi
@@ -20,18 +20,19 @@
 from groundlight_openapi_client.model.b_box_geometry_request import BBoxGeometryRequest
 from groundlight_openapi_client.model.channel_enum import ChannelEnum
 from groundlight_openapi_client.model.condition_request import ConditionRequest
+from groundlight_openapi_client.model.count_mode_configuration_serializer import CountModeConfigurationSerializer
 from groundlight_openapi_client.model.detector_group_request import DetectorGroupRequest
 from groundlight_openapi_client.model.label_value_request import LabelValueRequest
 from groundlight_openapi_client.model.roi_request import ROIRequest
 from groundlight_openapi_client.model.rule_request import RuleRequest
 from groundlight_openapi_client.model.verb_enum import VerbEnum
-from model import ROI, BBoxGeometry, Detector, DetectorGroup, ImageQuery, PaginatedRuleList, Rule
+from model import ROI, BBoxGeometry, Detector, DetectorGroup, ImageQuery, ModeEnum, PaginatedRuleList, Rule
 
 from groundlight.binary_labels import Label, convert_display_label_to_internal
 from groundlight.images import parse_supported_image_types
 from groundlight.optional_imports import Image, np
 
-from .client import Groundlight
+from .client import DEFAULT_REQUEST_TIMEOUT, Groundlight
 
 
 class ExperimentalApi(Groundlight):
@@ -305,3 +306,34 @@ def reset_detector(self, detector: Union[str, Detector]) -> None:
         if isinstance(detector, Detector):
             detector = detector.id
         self.detector_reset_api.reset_detector(detector)
+
+    def create_counting_detector(
+        self,
+        name: str,
+        query: str,
+        *,
+        max_count: Optional[int] = None,
+        group_name: Optional[str] = None,
+        confidence_threshold: Optional[float] = None,
+        patience_time: Optional[float] = None,
+        pipeline_config: Optional[str] = None,
+        metadata: Union[dict, str, None] = None,
+    ) -> Detector:
+        """
+        Creates a counting detector with the given name and query
+        """
+
+        detector_creation_input = self._prep_create_detector(
+            name=name,
+            query=query,
+            group_name=group_name,
+            confidence_threshold=confidence_threshold,
+            patience_time=patience_time,
+            pipeline_config=pipeline_config,
+            metadata=metadata,
+        )
+        detector_creation_input.mode = ModeEnum.COUNT
+        mode_config = CountModeConfigurationSerializer(max_count=max_count)
+        detector_creation_input.mode_configuration = mode_config
+        obj = self.detectors_api.create_detector(detector_creation_input, _request_timeout=DEFAULT_REQUEST_TIMEOUT)
+        return Detector.parse_obj(obj.to_dict())

test/unit/test_experimental.py

@@ -43,3 +43,13 @@ def test_submit_multiple_rois(gl_experimental: ExperimentalApi, image_query_no:
     label_name = "dog"
     roi = gl_experimental.create_roi(label_name, (0, 0), (0.5, 0.5))
     gl_experimental.add_label(image_query_no, "YES", [roi] * 3)
+
+def test_counting_detector(gl_experimental: ExperimentalApi):
+    """
+    verify that we can create and submit to a counting detector
+    """
+    name = f"Test {datetime.utcnow()}"
+    created_detector = gl_experimental.create_counting_detector(name, "How many dogs")
+    assert created_detector is not None
+    count_iq = gl_experimental.submit_image_query(created_detector, "test/assets/dog.jpeg")
+    assert count_iq.count is not None