init

app.py

@@ -1,10 +1,11 @@
 import numpy
 from sentence_transformers import SentenceTransformer, util
 from PIL import Image
-
+import gradio as gr
 
 model = SentenceTransformer('clip-ViT-B-32')
 
+
 def image_classifier(im1: numpy.ndarray, im2: numpy.ndarray):
     encoded_image = model.encode([Image.fromarray(im1), Image.fromarray(im2)], batch_size=128,
                                  convert_to_tensor=True, show_progress_bar=True)
@@ -12,7 +13,6 @@ def image_classifier(im1: numpy.ndarray, im2: numpy.ndarray):
     return processed_images[0][0]
 
 
-
 with gr.Blocks() as b:
     with gr.Row():
         with gr.Column():
@@ -23,5 +23,4 @@ with gr.Blocks() as b:
         output = gr.Label(label="output")
     compare.click(fn=image_classifier, inputs=[image1, image2], outputs=output)
 
-
-b.launch()
+b.launch()