fix

app.py

@@ -25,7 +25,6 @@ aesthetic_pipe = pipeline("image-classification",
                           torch_dtype=dtype)
 
 def predict(image, files=None):
-    print(image, files)
     images_paths = [image]
     if not files == None: 
         images_paths = list(map(lambda x: x.name, files))
@@ -35,12 +34,11 @@ def predict(image, files=None):
     aesthetic = aesthetic_pipe(pil_images)
     nsfw = nsfw_pipe(pil_images)
     results = [ a + b + c  for (a,b,c) in zip(style, aesthetic, nsfw)]
-    
     label_data = {}
-    if image:
-        label_data = [{ row["label"]:row["score"] for row in image } for image in results]
-                
-    return label_data[0], results
+    if image is not None:
+        label_data = { row["label"]:row["score"] for row in results[0] }
+    
+    return label_data, results
 
 with gr.Blocks() as blocks:
     with gr.Row():