Update app.py

app.py

@@ -8,14 +8,14 @@ model = ViTImageProcessor.from_pretrained('SeyedAli/Food-Image-Classification-VI
 
 def FoodClassification(image):
     with tempfile.NamedTemporaryFile(suffix=".png") as temp_audio_file:
-        # Copy the contents of the uploaded audio file to the temporary file
+        # Copy the contents of the uploaded image file to the temporary file
         temp_image_file.write(open(image, "rb").read())
         temp_image_file.flush()
         # Load the image file using torchvision
         image = read_image(temp_image_file.name)
         pipline = pipeline(task="image-classification", model=model)
         output=pipline(image, return_tensors='pt')
-            return output
+        return output
 
 iface = gr.Interface(fn=FoodClassification, inputs="image", outputs="text")
 iface.launch(share=False)