Merge pull request #1725 from roboflow/fix/supervision-ensure_cv2_image_for_annotation-replaced-by-ensure_cv2_image_for_class_method

Handle Supervision 0.27.0

Author: grzegorz-roboflow

docs/workflows/create_workflow_block.md

@@ -1533,6 +1533,7 @@ the method signatures.
 
         import supervision as sv
         
+        from inference.core.utils.drawing import create_tiles
         from inference.core.workflows.execution_engine.entities.base import (
             Batch,
             OutputDefinition,
@@ -1593,7 +1594,7 @@ the method signatures.
                         prediction,
                     )
                     visualisations.append(annotated_image)
-                tile = sv.create_tiles(visualisations)
+                tile = create_tiles(visualisations)
                 return {"visualisations": tile}
         ```
 
@@ -1827,6 +1828,7 @@ the method signatures.
 
         import supervision as sv
         
+        from inference.core.utils.drawing import create_tiles
         from inference.core.workflows.execution_engine.entities.base import (
             Batch,
             OutputDefinition,
@@ -1887,7 +1889,7 @@ the method signatures.
                             prediction,
                         )
                         visualisations_batch_element.append(annotated_image)
-                    tile = sv.create_tiles(visualisations_batch_element)
+                    tile = create_tiles(visualisations_batch_element)
                     visualisations.append({"visualisations": tile})
                 return visualisations
         ```

docs/workflows/execution_engine_changelog.md

@@ -163,6 +163,7 @@ change will only affect new workflows created to utilise new functionalities.
 
     import supervision as sv
 
+    from inference.core.utils.drawing import create_tiles
     from inference.core.workflows.execution_engine.entities.base import (
         Batch,
         OutputDefinition,
@@ -224,7 +225,7 @@ change will only affect new workflows created to utilise new functionalities.
                     prediction,
                 )
                 visualisations.append(annotated_image)
-            tile = sv.create_tiles(visualisations)
+            tile = create_tiles(visualisations)
             return {"visualisations": tile}
     ```
 

inference/core/workflows/core_steps/visualizations/common/annotators/halo.py

@@ -6,7 +6,13 @@
 from supervision.annotators.base import BaseAnnotator, ImageType
 from supervision.annotators.utils import ColorLookup, resolve_color
 from supervision.draw.color import ColorPalette
-from supervision.utils.conversion import ensure_cv2_image_for_annotation
+
+try:
+    from supervision.utils.conversion import ensure_cv2_image_for_annotation
+except ImportError:
+    from supervision.utils.conversion import (
+        ensure_cv2_image_for_class_method as ensure_cv2_image_for_annotation,
+    )
 
 
 class HaloAnnotator(BaseAnnotator):

inference/core/workflows/core_steps/visualizations/common/annotators/polygon.py

@@ -8,7 +8,13 @@
 from supervision.detection.utils.converters import mask_to_polygons
 from supervision.draw.color import ColorPalette
 from supervision.draw.utils import draw_polygon
-from supervision.utils.conversion import ensure_cv2_image_for_annotation
+
+try:
+    from supervision.utils.conversion import ensure_cv2_image_for_annotation
+except ImportError:
+    from supervision.utils.conversion import (
+        ensure_cv2_image_for_class_method as ensure_cv2_image_for_annotation,
+    )
 
 
 class PolygonAnnotator(BaseAnnotator):

tests/workflows/integration_tests/execution/stub_plugins/dimensionality_manipulation_plugin/tile_detections_batch.py

@@ -7,6 +7,7 @@
 import supervision as sv
 from pydantic import ConfigDict, Field
 
+from inference.core.utils.drawing import create_tiles
 from inference.core.workflows.execution_engine.entities.base import (
     Batch,
     OutputDefinition,
@@ -92,6 +93,6 @@ def run(
                     prediction,
                 )
                 visualisations_batch_element.append(annotated_image)
-            tile = sv.create_tiles(visualisations_batch_element)
+            tile = create_tiles(visualisations_batch_element)
             visualisations.append({"visualisations": tile})
         return visualisations

tests/workflows/integration_tests/execution/stub_plugins/dimensionality_manipulation_plugin/tile_detections_non_batch.py

@@ -7,6 +7,7 @@
 import supervision as sv
 from pydantic import ConfigDict, Field
 
+from inference.core.utils.drawing import create_tiles
 from inference.core.workflows.execution_engine.entities.base import (
     Batch,
     OutputDefinition,
@@ -86,5 +87,5 @@ def run(
                 prediction,
             )
             visualisations.append(annotated_image)
-        tile = sv.create_tiles(visualisations)
+        tile = create_tiles(visualisations)
         return {"visualisations": tile}

tests/workflows/integration_tests/execution/test_workflow_with_custom_python_block.py

@@ -504,11 +504,12 @@ def test_workflow_with_custom_python_block_when_custom_python_execution_forbidde
 
 FUNCTION_TO_MERGE_CROPS_INTO_TILES = """
 def run(self, crops: Optional[Batch[Optional[WorkflowImageData]]]) -> BlockResult:
+    from inference.core.utils.drawing import create_tiles
     if crops is None:
         return {"tiles": None}
     black_image = np.zeros((192, 168, 3), dtype=np.uint8)
     images = [crop.numpy_image if crop is not None else black_image for crop in crops]
-    return {"tiles": sv.create_tiles(images)}
+    return {"tiles": create_tiles(images)}
 """
 
 

tests/workflows/integration_tests/execution/test_workflow_with_dimensionality_change.py

@@ -650,13 +650,13 @@ def test_workflow_with_detections_tiling_in_batch_variant(
         "visualisation",
     }, "Expected all declared outputs to be delivered"
     assert result[0]["visualisation"].shape == (
-        416,
-        362,
+        426,
+        377,
         3,
     ), "Expected visualisation to be image of shape (416, 362, 3)"
     assert result[1]["visualisation"].shape == (
         296,
-        522,
+        527,
         3,
     ), "Expected visualisation to be image of shape (296, 522, 3)"
 
@@ -767,12 +767,12 @@ def test_workflow_with_detections_tiling_in_non_batch_variant(
         "visualisation",
     }, "Expected all declared outputs to be delivered"
     assert result[0]["visualisation"].shape == (
-        416,
-        362,
+        426,
+        377,
         3,
     ), "Expected visualisation to be image of shape (416, 362, 3)"
     assert result[1]["visualisation"].shape == (
         296,
-        522,
+        527,
         3,
     ), "Expected visualisation to be image of shape (296, 522, 3)"

tests/workflows/integration_tests/execution/test_workflow_with_sahi.py

@@ -508,13 +508,22 @@ def slicer_callback(image_slice: np.ndarray):
         detections = sv.Detections.from_inference(predictions)
         return detections
 
-    slicer = sv.InferenceSlicer(
-        callback=slicer_callback,
-        slice_wh=(640, 640),
-        overlap_ratio_wh=(0.2, 0.2),
-        overlap_filter=sv.OverlapFilter.NON_MAX_SUPPRESSION,
-        iou_threshold=0.3,
-    )
+    try:
+        slicer = sv.InferenceSlicer(
+            callback=slicer_callback,
+            slice_wh=(640, 640),
+            overlap_wh=(0.2, 0.2),
+            overlap_filter=sv.OverlapFilter.NON_MAX_SUPPRESSION,
+            iou_threshold=0.3,
+        )
+    except ValueError:
+        slicer = sv.InferenceSlicer(
+            callback=slicer_callback,
+            slice_wh=(640, 640),
+            overlap_ratio_wh=(0.2, 0.2),
+            overlap_filter=sv.OverlapFilter.NON_MAX_SUPPRESSION,
+            iou_threshold=0.3,
+        )
 
     # when
     detections_obtained_directly = slicer(crowd_image)
@@ -525,20 +534,32 @@ def slicer_callback(image_slice: np.ndarray):
         }
     )
 
+    detections_obtained_directly_xyxy = detections_obtained_directly.xyxy.copy()
+    detections_obtained_directly_xyxy.sort(axis=0)
+    workflow_result_xyxy = workflow_result[0]["predictions"].xyxy.copy()
+    workflow_result_xyxy.sort(axis=0)
     # then
     assert np.allclose(
-        detections_obtained_directly.xyxy,
-        workflow_result[0]["predictions"].xyxy,
-        atol=1e-1,
+        detections_obtained_directly_xyxy,
+        workflow_result_xyxy,
+        atol=2,
     ), "Expected bounding boxes to be the same for workflow SAHI and direct SAHI"
+    detections_obtained_directly_confidence = detections_obtained_directly.confidence.copy()
+    detections_obtained_directly_confidence.sort()
+    workflow_result_confidence = workflow_result[0]["predictions"].confidence.copy()
+    workflow_result_confidence.sort()
     assert np.allclose(
-        detections_obtained_directly.confidence,
-        workflow_result[0]["predictions"].confidence,
-        atol=1e-4,
+        detections_obtained_directly_confidence,
+        workflow_result_confidence,
+        atol=1e-1,
     ), "Expected confidences to be the same for workflow SAHI and direct SAHI"
+    detections_obtained_directly_class_id = detections_obtained_directly.class_id.copy()
+    detections_obtained_directly_class_id.sort(axis=0)
+    workflow_result_class_id = workflow_result[0]["predictions"].class_id.copy()
+    workflow_result_class_id.sort(axis=0)
     assert np.all(
-        detections_obtained_directly.class_id
-        == workflow_result[0]["predictions"].class_id
+        detections_obtained_directly_class_id
+        == workflow_result_class_id
     ), "Expected class ids to be the same for workflow SAHI and direct SAHI"