Debugging over the wire step

src/groundlight/client.py

@@ -19,6 +19,7 @@
     ImageQuery,
     PaginatedDetectorList,
     PaginatedImageQueryList,
+    ROI,
 )
 from urllib3.exceptions import InsecureRequestWarning
 
@@ -726,7 +727,7 @@ def _wait_for_result(
             image_query = self._fixup_image_query(image_query)
         return image_query
 
-    def add_label(self, image_query: Union[ImageQuery, str], label: Union[Label, str], rois: Optional[list] = None):
+    def add_label(self, image_query: Union[ImageQuery, str], label: Union[Label, str], rois: Optional[list[ROI]] = None):
         """
         Add a new label to an image query.  This answers the detector's question.
 
@@ -747,8 +748,8 @@ def add_label(self, image_query: Union[ImageQuery, str], label: Union[Label, str
             if not image_query_id.startswith(("chk_", "iq_")):
                 raise ValueError(f"Invalid image query id {image_query_id}")
         api_label = convert_display_label_to_internal(image_query_id, label)
-        json_rois = [roi.json() for roi in rois] if rois else None
-        request_params = LabelValueRequest(label=api_label, image_query_id=image_query_id, rois=json_rois)
+        request_params = LabelValueRequest(label=api_label, image_query_id=image_query_id, rois=rois)
+        import IPython; IPython.embed()
         self.labels_api.create_label(request_params)
 
     def start_inspection(self) -> str:

src/groundlight/experimental_api.py

@@ -20,7 +20,7 @@
 from groundlight_openapi_client.model.note_request import NoteRequest
 from groundlight_openapi_client.model.rule_request import RuleRequest
 from groundlight_openapi_client.model.verb_enum import VerbEnum
-from model import Detector, DetectorGroup, PaginatedRuleList, Rule, ROI
+from model import Detector, DetectorGroup, PaginatedRuleList, Rule, ROI, BBoxGeometry
 
 from .client import Groundlight
 
@@ -201,3 +201,27 @@ def list_detector_groups(self) -> List[DetectorGroup]:
         :return: a list of all detector groups
         """
         return [DetectorGroup(**det.to_dict()) for det in self.detector_group_api.get_detector_groups()]
+
+    def create_roi(self, label: str, top_left: Tuple[int, int], bottom_right: Tuple[int, int]) -> ROI:
+        """
+        Adds a region of interest to the given detector
+        NOTE: This feature is only available to Pro tier and higher
+        If you would like to learn more, reach out to us at https://groundlight.ai
+
+        :param label: the label of the item in the roi
+        :param top_left: the top left corner of the roi
+        :param bottom_right: the bottom right corner of the roi
+        """
+
+        return ROI(
+            label=label,
+            score=1.0,
+            geometry=BBoxGeometry(
+                left = top_left[0],
+                top = top_left[1],
+                right = bottom_right[0],
+                bottom = bottom_right[1],
+                x = (top_left[0] + bottom_right[0]) / 2,
+                y = (top_left[1] + bottom_right[1]) / 2,
+            )
+        )

test/integration/test_groundlight.py

@@ -64,35 +64,6 @@ def is_valid_display_label(label: str) -> bool:
     return label in VALID_DISPLAY_LABELS
 
 
-@pytest.fixture(name="gl")
-def fixture_gl() -> Groundlight:
-    """Creates a Groundlight client object for testing."""
-    _gl = Groundlight()
-    _gl.DEFAULT_WAIT = 10
-    return _gl
-
-
-@pytest.fixture(name="detector")
-def fixture_detector(gl: Groundlight) -> Detector:
-    """Creates a new Test detector."""
-    name = f"Test {datetime.utcnow()}"  # Need a unique name
-    query = "Is there a dog?"
-    pipeline_config = "never-review"
-    return gl.create_detector(name=name, query=query, pipeline_config=pipeline_config)
-
-
-@pytest.fixture(name="image_query_yes")
-def fixture_image_query_yes(gl: Groundlight, detector: Detector) -> ImageQuery:
-    iq = gl.submit_image_query(detector=detector.id, image="test/assets/dog.jpeg", human_review="NEVER")
-    return iq
-
-
-@pytest.fixture(name="image_query_no")
-def fixture_image_query_no(gl: Groundlight, detector: Detector) -> ImageQuery:
-    iq = gl.submit_image_query(detector=detector.id, image="test/assets/cat.jpeg", human_review="NEVER")
-    return iq
-
-
 @pytest.fixture(name="image")
 def fixture_image() -> str:
     return "test/assets/dog.jpeg"

test/unit/conftest.py

@@ -1,7 +1,33 @@
 import pytest
-from groundlight import ExperimentalApi
+from datetime import datetime
 
+from groundlight import ExperimentalApi, Groundlight, Detector, ImageQuery
 
 @pytest.fixture(name="gl")
+def fixture_gl() -> Groundlight:
+    """Creates a Groundlight client object for testing."""
+    _gl = Groundlight()
+    _gl.DEFAULT_WAIT = 10
+    return _gl
+
+@pytest.fixture(name="detector")
+def fixture_detector(gl: Groundlight) -> Detector:
+    """Creates a new Test detector."""
+    name = f"Test {datetime.utcnow()}"  # Need a unique name
+    query = "Is there a dog?"
+    pipeline_config = "never-review"
+    return gl.create_detector(name=name, query=query, pipeline_config=pipeline_config)
+
+@pytest.fixture(name="image_query_yes")
+def fixture_image_query_yes(gl: Groundlight, detector: Detector) -> ImageQuery:
+    iq = gl.submit_image_query(detector=detector.id, image="test/assets/dog.jpeg", human_review="NEVER")
+    return iq
+
+@pytest.fixture(name="image_query_no")
+def fixture_image_query_no(gl: Groundlight, detector: Detector) -> ImageQuery:
+    iq = gl.submit_image_query(detector=detector.id, image="test/assets/cat.jpeg", human_review="NEVER")
+    return iq
+
+@pytest.fixture(name="gl_experimental")
 def _gl() -> ExperimentalApi:
     return ExperimentalApi()

test/unit/test_experimental.py

@@ -1,13 +1,28 @@
 from datetime import datetime
 
-from groundlight import ExperimentalApi
+from groundlight import ExperimentalApi, Detector, ImageQuery, ROI
 
-
-def test_detector_groups(gl: ExperimentalApi):
+def test_detector_groups(gl_experimental: ExperimentalApi):
     """
     verify that we can create a detector group and retrieve it
     """
     name = f"Test {datetime.utcnow()}"
-    created_group = gl.create_detector_group(name)
-    all_groups = gl.list_detector_groups()
+    created_group = gl_experimental.create_detector_group(name)
+    all_groups = gl_experimental.list_detector_groups()
     assert created_group in all_groups
+
+def test_submit_roi(gl_experimental: ExperimentalApi, image_query_yes: ImageQuery):
+    """
+    verify that we can submit an ROI
+    """
+    label_name = "dog"
+    roi = gl_experimental.create_roi(label_name, (0, 0), (0.5, 0.5))
+    gl_experimental.add_label(image_query_yes.id, "YES", [roi])
+
+def test_submit_rois(gl_experimental: ExperimentalApi, image_query_no: ImageQuery):
+    """
+    verify that we can submit multiple ROIs
+    """
+    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)