Update load image

app.py

@@ -43,12 +43,33 @@ class GOSNormalize(object):
 
 transform =  transforms.Compose([GOSNormalize([0.5,0.5,0.5],[1.0,1.0,1.0])])
 
-def load_image(im_path, hypar):
-    im = im_reader(im_path)
+def load_image(image, hypar):
+    """
+    Load and preprocess an image.
+    :param image: The image to load. This can be either a file path or a PIL.Image object.
+    :param hypar: Hyperparameters for preprocessing.
+    :return: A tuple of the preprocessed image tensor and its original shape.
+    """
+    # Check if the image is a file path or a PIL.Image object
+    if isinstance(image, str):
+        # If it's a file path, read the image from disk
+        im = im_reader(image)
+    elif isinstance(image, Image.Image):
+        # If it's a PIL.Image object, convert it to a NumPy array
+        im = np.array(image)
+    else:
+        raise TypeError("Unsupported image type")
+
+    # Preprocess the image
     im, im_shp = im_preprocess(im, hypar["cache_size"])
-    im = torch.divide(im,255.0)
+    im = torch.divide(im, 255.0)
     shape = torch.from_numpy(np.array(im_shp))
-    return transform(im).unsqueeze(0), shape.unsqueeze(0) # make a batch of image, shape
+
+    # Normalize and add batch dimension
+    im = transform(im).unsqueeze(0)
+    shape = shape.unsqueeze(0)  # Add batch dimension to shape
+
+    return im, shape
 
 
 def build_model(hypar,device):