Merge pull request #1616 from roboflow/fix/image-preprocessing-dynamic-params

Fix image preprocessing block to accept dynamic parameter references

Author: PawelPeczek-Roboflow

inference/core/workflows/core_steps/classical_cv/image_preprocessing/v1.py

@@ -2,7 +2,7 @@
 
 import cv2
 import numpy as np
-from pydantic import AliasChoices, ConfigDict, Field
+from pydantic import AliasChoices, ConfigDict, Field, PositiveInt
 
 from inference.core.workflows.execution_engine.entities.base import (
     OutputDefinition,
@@ -55,12 +55,11 @@ class ImagePreprocessingManifest(WorkflowBlockManifest):
     task_type: Literal["resize", "rotate", "flip"] = Field(
         description="Preprocessing task to be applied to the image.",
     )
-    width: Union[int, Selector(kind=[INTEGER_KIND])] = Field(  # type: ignore
+    width: Union[PositiveInt, Selector(kind=[INTEGER_KIND])] = Field(  # type: ignore
         title="Width",
         default=640,
         description="Width of the image to be resized to.",
         examples=[640, "$inputs.resize_width"],
-        gt=0,
         json_schema_extra={
             "relevant_for": {
                 "task_type": {
@@ -70,12 +69,11 @@ class ImagePreprocessingManifest(WorkflowBlockManifest):
             },
         },
     )
-    height: Union[int, Selector(kind=[INTEGER_KIND])] = Field(  # type: ignore
+    height: Union[PositiveInt, Selector(kind=[INTEGER_KIND])] = Field(  # type: ignore
         title="Height",
         default=640,
         description="Height of the image to be resized to.",
         examples=[640, "$inputs.resize_height"],
-        gt=0,
         json_schema_extra={
             "relevant_for": {
                 "task_type": {
@@ -90,8 +88,6 @@ class ImagePreprocessingManifest(WorkflowBlockManifest):
         description="Positive value to rotate clockwise, negative value to rotate counterclockwise",
         default=90,
         examples=[90, "$inputs.rotation_degrees"],
-        ge=-360,
-        le=360,
         json_schema_extra={
             "relevant_for": {
                 "task_type": {
@@ -101,7 +97,9 @@ class ImagePreprocessingManifest(WorkflowBlockManifest):
             }
         },
     )
-    flip_type: Union[Selector(kind=[STRING_KIND]), Literal["vertical", "horizontal", "both"]] = Field(  # type: ignore
+    flip_type: Union[
+        Selector(kind=[STRING_KIND]), Literal["vertical", "horizontal", "both"]
+    ] = Field(  # type: ignore
         title="Flip Type",
         description="Type of flip to be applied to the image.",
         default="vertical",
@@ -150,10 +148,24 @@ def run(
         response_image = None
 
         if task_type == "resize":
+            if width is not None and width <= 0:
+                raise ValueError("Width must be greater than 0")
+            if height is not None and height <= 0:
+                raise ValueError("Height must be greater than 0")
             response_image = apply_resize_image(image.numpy_image, width, height)
         elif task_type == "rotate":
+            if rotation_degrees is not None and not (-360 <= rotation_degrees <= 360):
+                raise ValueError("Rotation degrees must be between -360 and 360")
             response_image = apply_rotate_image(image.numpy_image, rotation_degrees)
         elif task_type == "flip":
+            if flip_type is not None and flip_type not in [
+                "vertical",
+                "horizontal",
+                "both",
+            ]:
+                raise ValueError(
+                    "Flip type must be 'vertical', 'horizontal', or 'both'"
+                )
             response_image = apply_flip_image(image.numpy_image, flip_type)
         else:
             raise ValueError(f"Invalid task type: {task_type}")

tests/workflows/integration_tests/execution/test_workflow_with_image_preprocessing.py

@@ -194,6 +194,73 @@ def test_rotate_image_workflow_when_valid_input_provided(
     ), "Expected image to be rotated 90 degrees"
 
 
+def test_rotate_image_workflow_with_dynamic_rotation_degrees(
+    model_manager: ModelManager,
+    dogs_image: np.ndarray,
+) -> None:
+    """Test that rotation_degrees can accept dynamic parameter references."""
+    # given
+    workflow_definition = {
+        "version": "1.0",
+        "inputs": [
+            {"type": "InferenceImage", "name": "image"},
+            {"type": "WorkflowParameter", "name": "rotation_angle", "default_value": 90},
+        ],
+        "steps": [
+            {
+                "type": "roboflow_core/image_preprocessing@v1",
+                "name": "rotate",
+                "image": "$inputs.image",
+                "task_type": "rotate",
+                "rotation_degrees": "$inputs.rotation_angle",
+            }
+        ],
+        "outputs": [
+            {
+                "type": "JsonField",
+                "name": "rotated_image",
+                "coordinates_system": "own",
+                "selector": "$steps.rotate.image",
+            }
+        ],
+    }
+
+    workflow_init_parameters = {
+        "workflows_core.model_manager": model_manager,
+        "workflows_core.api_key": None,
+        "workflows_core.step_execution_mode": StepExecutionMode.LOCAL,
+    }
+    execution_engine = ExecutionEngine.init(
+        workflow_definition=workflow_definition,
+        init_parameters=workflow_init_parameters,
+        max_concurrent_steps=WORKFLOWS_MAX_CONCURRENT_STEPS,
+    )
+
+    # when
+    result = execution_engine.run(
+        runtime_parameters={
+            "image": dogs_image,
+            "rotation_angle": 180,
+        }
+    )
+
+    # then
+    original_image_height, original_image_width, _ = dogs_image.shape
+    assert isinstance(result, list), "Expected list to be delivered"
+    assert len(result) == 1, "Expected 1 element in the output for one input image"
+    assert set(result[0].keys()) == {
+        "rotated_image",
+    }, "Expected all declared outputs to be delivered"
+    np_image = result[0]["rotated_image"].numpy_image
+    # 180 degree rotation should preserve dimensions
+    assert (
+        np_image.shape[0] == original_image_height
+    ), "Expected image height to be preserved after 180 degree rotation"
+    assert (
+        np_image.shape[1] == original_image_width
+    ), "Expected image width to be preserved after 180 degree rotation"
+
+
 def test_rotate_image_workflow_when_missing_required_parameters() -> None:
     # given
     data = {