Update app.py

app.py

@@ -3,11 +3,23 @@ import kornia as K
 from kornia.core import Tensor
 from kornia import morphology as morph
 import torch
+import numpy as np
 
 def morphological_operators(img, operator, kernel, kernel_size): 
-    img: Tensor = K.io.image_to_tensor(img)
+    # Convert input to tensor
+    if isinstance(img, np.ndarray):
+        img = torch.from_numpy(img).permute(2, 0, 1).float() / 255.0
+    elif isinstance(img, torch.Tensor):
+        img = img.permute(2, 0, 1).float()
+        if img.max() > 1.0:
+            img = img / 255.0
+    else:
+        raise ValueError(f"Unsupported image type: {type(img)}")
+
     img = img.unsqueeze(0)  # Add batch dimension
     device = 'cpu'  # 'cuda:0' for GPU
+    img = img.to(device)
+
     kernels = {
         "Ones": torch.ones(kernel_size, kernel_size).to(device),
         "Eye": torch.eye(kernel_size).to(device),
@@ -30,7 +42,6 @@ examples = [
     ["examples/cat.png", "Dilation", "Ones", 3],
     ["examples/huggingface.jpg", "Close", "Eye", 5]
 ]
-
 title = "Kornia Morphological Operators"
 description = "<p style='text-align: center'>This is a Gradio demo for Kornia's Morphological Operators.</p><p style='text-align: center'>To use it, simply upload your image, or click one of the examples to load them, and select any morphological operator to run it! Read more at the links at the bottom.</p>"
 article = "<p style='text-align: center'><a href='https://kornia.readthedocs.io/en/latest/' target='_blank'>Kornia Docs</a> | <a href='https://github.com/kornia/kornia' target='_blank'>Kornia Github Repo</a> | <a href='https://kornia-tutorials.readthedocs.io/en/latest/morphology_101.html' target='_blank'>Kornia Morphological Operators Tutorial</a></p>"