numpy not needed

app.py

@@ -1,9 +1,7 @@
 import gradio as gr
 
 import kornia as K
-from kornia.core import Tensor
-
-import numpy as np
+from kornia.core import concatenate, Tensor
 
 def rescale_aa(file, height, width):
     
@@ -12,13 +10,10 @@ def rescale_aa(file, height, width):
 
     img_rescale: Tensor = K.geometry.rescale(img, (float(height),float(width)),antialias=False)
     img_rescale_aa: Tensor = K.geometry.rescale(img, (float(height),float(width)),antialias=True)
-    img_rescale = K.utils.tensor_to_image(img_rescale)
-    img_rescale_aa = K.utils.tensor_to_image(img_rescale_aa)
-    img_out = np.concatenate([img_rescale,img_rescale_aa],axis=1)
+    img_out = concatenate([img_rescale, img_rescale_aa], -1)
     
     # when antialiasing , some values are going greater than 1 i.e 1.00001 which is giving error while displaying the output image,so clipping the output values from 0 to 1
-    return np.clip(img_out ,0,1)
-
+    return K.utils.tensor_to_image(img_out.clamp_(0, 1))
 
 examples = [
     ["examples/a.png",1,1],