Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import torch
 import kornia as K
+from kornia.geometry.transform import resize
 import cv2
 import numpy as np
 from torchvision import transforms
@@ -8,18 +9,16 @@ from torchvision.utils import make_grid
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-def resize_images(f_names):
-    for i, f_name in enumerate(f_names):
-      img = cv2.imread(f_name, cv2.IMREAD_COLOR)
-      resized_image = cv2.resize(img,(50, 50))
-      cv2.imwrite(f_name,resized_image)
+def read_image(f_name):
+      image_to_tensor = transforms.ToTensor()
+      img = image_to_tensor(cv2.imread(f_name, cv2.IMREAD_COLOR))
+      resized_image = resize(img,(50, 50))
+      return resized_image
 
 def predict(images, eps):
   eps = float(eps)
   f_names = [img.name for img in images]
-  resize_images(f_names)
-  convert_tensor = transforms.ToTensor()
-  images = [convert_tensor(cv2.imread(f, cv2.IMREAD_COLOR)) for f in f_names]
+  images = [read_image(f) for f in f_names]
   images = torch.stack(images, dim = 0).to(device) 
   zca = K.enhance.ZCAWhitening(eps=eps, compute_inv=True)
   zca.fit(images)
@@ -29,7 +28,7 @@ def predict(images, eps):
 
 title = 'ZCA Whitening with Kornia!'
 description = '''[ZCA Whitening](https://paperswithcode.com/method/zca-whitening) is an image preprocessing method that leads to a transformation of data such that the covariance matrix is the identity matrix, leading to decorrelated features:
-*Note that you can upload only image files, e.g. jpg, png etc and there should be atleast 2 images!* 
+*Note that you can upload only image files, e.g. jpg, png etc and there sjould be atleast 2 images!* 
 Learn more about [ZCA Whitening and Kornia](https://kornia.readthedocs.io/en/latest/_modules/kornia/enhance/zca.html)'''
 
 iface = gr.Interface(fn=predict, 
@@ -40,19 +39,17 @@ iface = gr.Interface(fn=predict,
              description=description,
              examples=[[
                  [
-                  'irises.jpg', 
-                  'roses.jpg', 
-                  'sunflower.jpg',
-                  'violets.jpg', 
-                  'chamomile.jpg', 
-                  'tulips.jpg', 
-                  'Alstroemeria.jpg', 
-                  'Carnation.jpg', 
-                  'Orchid.jpg', 
-                  'Peony.jpg',
-                  'Aster.jpg',
-                  'Dahlia.jpg'
-                  ], 0.1]]
+                  '/content/irises.jpg', 
+                  '/content/roses.jpg', 
+                  '/content/sunflower.jpg',
+                  '/content/violets.jpg', 
+                  '/content/chamomile.jpg', 
+                  '/content/tulips.jpg', 
+                  '/content/Alstroemeria.jpg', 
+                  '/content/Carnation.jpg', 
+                  '/content/Orchid.jpg', 
+                  '/content/Peony.jpg'
+                  ], 0.01]]
              )
 
 if __name__ == "__main__":