added ImageStitcher parameters

app.py

@@ -1,14 +1,16 @@
 import gradio as gr
 import kornia as K
-from kornia.core import Tensor
-
-
-def enhance(file):      
-    # load the image using the rust backend          
-    img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
-    img = img[None]  # 1xCxHxW / fp32 / [0, 1]
-    return K.utils.tensor_to_image(img)
+from skimage import io
+from kornia.contrib import ImageStitcher
+import kornia.feature as KF
 
+def enhance(file_1, file_2):   
+    img_1 = K.image_to_tensor(io.imread(file_1), False).float() / 255.
+    img_2 = K.image_to_tensor(io.imread(file_2), False).float() / 255.
+    IS = ImageStitcher(KF.LoFTR(pretrained='outdoor'), estimator='ransac')
+    result = IS(img_1, img_2)
+    return K.tensor_to_image(result[0])
+    
 
 examples = [
     ['examples/foto1B.jpg'],
@@ -16,17 +18,23 @@ examples = [
 ]
 
 
-iface = gr.Interface(
-    enhance,
-    [
-        gr.inputs.Image(type="file"),
-    ],
-    "image",
+inputs = [
+    gr.inputs.Image(type='file', label='Input Image'),
+    gr.inputs.Image(type='file', label='Input Image'),
+]
+
+outputs = [
+    gr.outputs.Image(type='file', label='Output Image'),
+
+]
+
+title = "Image Stitching using Kornia and LoFTR"
+
+demo_app = gr.Interface(
+    fn=enhance,
+    inputs=inputs,
+    outputs=outputs,
+    title=title,
     examples=examples,
-    # title=title,
-    # description=description,
-    # article=article,
-    live=True
 )
-
-iface.launch()
+demo_app.launch()