updated mock Image object (#670)

* updated mock object

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* added property to cls variable

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* refactor PR

* merge

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

flash/core/utilities/imports.py

@@ -17,6 +17,7 @@
 import types
 from importlib.util import find_spec
 from typing import Callable, List, Union
+from warnings import warn
 
 from pkg_resources import DistributionNotFound
 
@@ -99,6 +100,25 @@ def _compare_version(package: str, op, version) -> bool:
 _ICEDATA_AVAILABLE = _module_available("icedata")
 _TORCH_ORT_AVAILABLE = _module_available("torch_ort")
 
+if _PIL_AVAILABLE:
+    from PIL import Image
+else:
+
+    class MetaImage(type):
+        def __init__(cls, name, bases, dct):
+            super().__init__(name, bases, dct)
+
+            cls._Image = None
+
+        @property
+        def Image(cls):
+            warn("Mock object called due to missing PIL library. Please use \"pip install 'lightning-flash[image]'\".")
+            return cls._Image
+
+    class Image(metaclass=MetaImage):
+        pass
+
+
 if Version:
     _TORCHVISION_GREATER_EQUAL_0_9 = _compare_version("torchvision", operator.ge, "0.9.0")
 

flash/image/classification/data.py

@@ -24,7 +24,7 @@
 from flash.core.data.data_module import DataModule
 from flash.core.data.data_source import DefaultDataKeys, DefaultDataSources, LoaderDataFrameDataSource
 from flash.core.data.process import Deserializer, Preprocess
-from flash.core.utilities.imports import _MATPLOTLIB_AVAILABLE, _PIL_AVAILABLE, requires, requires_extras
+from flash.core.utilities.imports import _MATPLOTLIB_AVAILABLE, Image, requires, requires_extras
 from flash.image.classification.transforms import default_transforms, train_default_transforms
 from flash.image.data import (
     image_loader,
@@ -40,13 +40,6 @@
 else:
     plt = None
 
-if _PIL_AVAILABLE:
-    from PIL import Image
-else:
-
-    class Image:
-        Image = None
-
 
 class ImageClassificationDataFrameDataSource(LoaderDataFrameDataSource):
     @requires_extras("image")

flash/image/data.py

@@ -29,7 +29,7 @@
     TensorDataSource,
 )
 from flash.core.data.process import Deserializer
-from flash.core.utilities.imports import _PIL_AVAILABLE, _TORCHVISION_AVAILABLE, requires_extras
+from flash.core.utilities.imports import _TORCHVISION_AVAILABLE, Image, requires_extras
 
 if _TORCHVISION_AVAILABLE:
     import torchvision
@@ -38,13 +38,6 @@
 else:
     IMG_EXTENSIONS = ()
 
-if _PIL_AVAILABLE:
-    from PIL import Image as PILImage
-else:
-
-    class Image:
-        Image = None
-
 
 NP_EXTENSIONS = (".npy", ".npz")
 
@@ -53,7 +46,7 @@ def image_loader(filepath: str):
     if has_file_allowed_extension(filepath, IMG_EXTENSIONS):
         img = default_loader(filepath)
     elif has_file_allowed_extension(filepath, NP_EXTENSIONS):
-        img = PILImage.fromarray(np.load(filepath).astype("uint8"), "RGB")
+        img = Image.fromarray(np.load(filepath).astype("uint8"), "RGB")
     else:
         raise ValueError(
             f"File: {filepath} has an unsupported extension. Supported extensions: "
@@ -72,7 +65,7 @@ def deserialize(self, data: str) -> Dict:
         encoded_with_padding = (data + "===").encode("ascii")
         img = base64.b64decode(encoded_with_padding)
         buffer = BytesIO(img)
-        img = PILImage.open(buffer, mode="r")
+        img = Image.open(buffer, mode="r")
         return {
             DefaultDataKeys.INPUT: img,
         }

flash/image/segmentation/data.py

@@ -38,8 +38,8 @@
 from flash.core.utilities.imports import (
     _FIFTYONE_AVAILABLE,
     _MATPLOTLIB_AVAILABLE,
-    _PIL_AVAILABLE,
     _TORCHVISION_AVAILABLE,
+    Image,
     lazy_import,
     requires,
     requires_extras,
@@ -68,13 +68,6 @@
 else:
     IMG_EXTENSIONS = None
 
-if _PIL_AVAILABLE:
-    from PIL import Image
-else:
-
-    class Image:
-        Image = None
-
 
 class SemanticSegmentationNumpyDataSource(NumpyDataSource):
     def load_sample(self, sample: Dict[str, Any], dataset: Optional[Any] = None) -> Dict[str, Any]:

tests/core/test_model.py

@@ -32,7 +32,7 @@
 from flash.core.adapter import Adapter
 from flash.core.classification import ClassificationTask
 from flash.core.data.process import DefaultPreprocess, Postprocess
-from flash.core.utilities.imports import _PIL_AVAILABLE, _TABULAR_AVAILABLE, _TEXT_AVAILABLE
+from flash.core.utilities.imports import _TABULAR_AVAILABLE, _TEXT_AVAILABLE, Image
 from flash.image import ImageClassificationData, ImageClassifier
 from tests.helpers.utils import _IMAGE_TESTING, _TABULAR_TESTING
 
@@ -41,13 +41,6 @@
 else:
     TabularClassifier = None
 
-if _PIL_AVAILABLE:
-    from PIL import Image
-else:
-
-    class Image:
-        Image = None
-
 
 # ======== Mock functions ========