diff --git a/inference/core/workflows/core_steps/transformations/perspective_correction/v1.py b/inference/core/workflows/core_steps/transformations/perspective_correction/v1.py
index c82d222ea3..7d0df03e5f 100644
--- a/inference/core/workflows/core_steps/transformations/perspective_correction/v1.py
+++ b/inference/core/workflows/core_steps/transformations/perspective_correction/v1.py
@@ -406,11 +406,15 @@ def run(
             result_image = image
             if warp_image:
                 # https://docs.opencv.org/4.9.0/da/d54/group__imgproc__transform.html#gaf73673a7e8e18ec6963e3774e6a94b87
-                result_image = cv.warpPerspective(
+                warped_image = cv.warpPerspective(
                     src=image.numpy_image,
                     M=perspective_transformer,
                     dsize=(transformed_rect_width, transformed_rect_height),
                 )
+                result_image = WorkflowImageData(
+                    parent_metadata=image.parent_metadata,
+                    numpy_image=warped_image,
+                )
 
             if detections is None:
                 result.append(
diff --git a/tests/workflows/unit_tests/core_steps/transformations/test_perspective_correction.py b/tests/workflows/unit_tests/core_steps/transformations/test_perspective_correction.py
index d7b381d0b7..ae7a8f626e 100644
--- a/tests/workflows/unit_tests/core_steps/transformations/test_perspective_correction.py
+++ b/tests/workflows/unit_tests/core_steps/transformations/test_perspective_correction.py
@@ -14,8 +14,15 @@
 from inference.core.workflows.execution_engine.constants import (
     KEYPOINTS_XY_KEY_IN_SV_DETECTIONS,
 )
-from inference.core.workflows.execution_engine.entities.base import Batch
+from inference.core.workflows.execution_engine.entities.base import (
+    Batch,
+    WorkflowImageData,
+    ImageParentMetadata
+)
 
+from inference.core.workflows.core_steps.transformations.perspective_correction.v1 import (
+    PerspectiveCorrectionBlockV1,
+)
 
 @pytest.mark.parametrize("broken_input", [1, "cat", np.array([])])
 def test_pick_largest_perspective_polygons_raises_on_unexpected_type_of_input(
@@ -286,3 +293,27 @@ def test_correct_detections_with_keypoints():
         dtype="object",
     )
     assert corrected_detections == expected_detections
+
+
+def test_warp_image():
+    # given
+    dummy_image = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
+    dummy_predictions = sv.Detections(xyxy=np.array([[10, 10, 20, 20]]))
+    perspective_correction_block = PerspectiveCorrectionBlockV1()
+
+    workflow_image_data = WorkflowImageData(parent_metadata=ImageParentMetadata(parent_id="test"), numpy_image=dummy_image)
+
+    # when
+    result = perspective_correction_block.run(
+        images=[workflow_image_data],
+        predictions=[dummy_predictions],
+        perspective_polygons=[[[1, 1], [99, 1], [99, 99], [1, 99]]],
+        transformed_rect_width=200,
+        transformed_rect_height=200,
+        extend_perspective_polygon_by_detections_anchor=None,
+        warp_image=True,
+    )
+
+    # then
+    assert "warped_image" in result[0], "warped_image key must be present in the result"
+    assert isinstance(result[0]["warped_image"], WorkflowImageData), f"warped_image must be of type WorkflowImageData"