Update scikit-learn requirement in SklearnIntegration

src/zenml/integrations/sklearn/__init__.py

@@ -21,12 +21,12 @@ class SklearnIntegration(Integration):
     """Definition of sklearn integration for ZenML."""
 
     NAME = SKLEARN
-    REQUIREMENTS = ["scikit-learn", "scikit-image"]
+    REQUIREMENTS = ["scikit-learn"]
 
     @classmethod
     def activate(cls) -> None:
         """Activates the integration."""
         from zenml.integrations.sklearn import materializers  # noqa
 
-SklearnIntegration.check_installation()
 
+SklearnIntegration.check_installation()

tests/integration/examples/mlflow/steps/dynamic_importer_step.py

@@ -1,3 +1,5 @@
+"""This step downloads the latest data from a mock API and returns it as a numpy array."""
+
 #  Copyright (c) ZenML GmbH 2022. All Rights Reserved.
 #
 #  Licensed under the Apache License, Version 2.0 (the "License");
@@ -14,13 +16,17 @@
 import numpy as np  # type: ignore [import]
 import pandas as pd  # type: ignore [import]
 import requests  # type: ignore [import]
-from skimage.transform import resize
 from typing_extensions import Annotated
 
 from zenml import step
 
 
-def get_data_from_api():
+def get_data_from_api() -> Annotated[np.ndarray, "api_data"]:
+    """Downloads the latest data from a mock API.
+
+    Returns:
+        Annotated[np.ndarray, "data"]: Downsampled image data as a numpy array.
+    """
     url = (
         "https://storage.googleapis.com/zenml-public-bucket/mnist"
         "/mnist_handwritten_test.json"
@@ -30,12 +36,10 @@ def get_data_from_api():
     data = df["image"].map(lambda x: np.array(x)).values
     data = np.array(
         [
-            resize(
-                x.reshape(28, 28).astype("uint8"),
-                (8, 8),
-                anti_aliasing=False,
-                preserve_range=True,
-            )
+            # Pad the image to 32x32 to enable downsampling to 8x8
+            np.pad(x.reshape(28, 28).astype("float64"), 2)[
+                ::4, ::4
+            ]  # Downsample to 8x8 by taking every 4th pixel
             for x in data
         ]
     )
@@ -44,6 +48,10 @@ def get_data_from_api():
 
 @step(enable_cache=False)
 def dynamic_importer() -> Annotated[np.ndarray, "data"]:
-    """Downloads the latest data from a mock API."""
+    """Downloads the latest data from a mock API.
+
+    Returns:
+        Annotated[np.ndarray, "data"]: Downsampled image data as a numpy array.
+    """
     data = get_data_from_api()
     return data