Using Colab friendly array to image conversion

DeOldify_colab.ipynb

@@ -496,24 +496,6 @@
     "!mkdir \"/content/drive/My Drive/deOldifyImages/results\""
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {},
-    "colab_type": "code",
-    "id": "695Tr-7IIFm5"
-   },
-   "outputs": [],
-   "source": [
-    "# workaround for saving images from colab (source https://stackoverflow.com/questions/48547660/attributeerror-module-pil-image-has-no-attribute-register-extensions) \n",
-    "def register_extension(id, extension): Image.EXTENSION[extension.lower()] = id.upper()\n",
-    "Image.register_extension = register_extension\n",
-    "def register_extensions(id, extensions): \n",
-    "  for extension in extensions: register_extension(id, extension)\n",
-    "Image.register_extensions = register_extensions"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

fasterai/visualize.py

@@ -37,11 +37,15 @@ class ModelImageVisualizer():
     def get_transformed_image_as_pil(self, path:str, model:nn.Module, sz:int=None, tfms:[Transform]=[])->Image:
         path = Path(path)
         array = self.get_transformed_image_ndarray(path, model, sz, tfms=tfms)
-        return misc.toimage(array)
+        return self._convert_array_to_pil_image(array)
+
+    def _convert_array_to_pil_image(self, array:ndarray):
+        return Image.fromarray((array*255).astype('uint8'))
 
     def _save_result_image(self, source_path:Path, result:ndarray):
         result_path = self.results_dir/source_path.name
-        misc.imsave(result_path, result)
+        im = self._convert_array_to_pil_image(result)
+        im.save(result_path)
 
     def plot_images_from_image_sets(self, image_sets:[ModelImageSet], validation:bool, figsize:(int,int)=(20,20), 
             max_columns:int=6, immediate_display:bool=True):