finish

app.py

@@ -14,6 +14,7 @@ model = TFSegformerForSemanticSegmentation.from_pretrained(
     "nvidia/segformer-b3-finetuned-cityscapes-1024-1024"
 )
 
+
 def ade_palette():
     """ADE20K palette that maps each class to RGB values."""
     return [
@@ -35,9 +36,10 @@ def ade_palette():
         [153, 138, 0],
         [71, 102, 0],
         [47, 157, 39],
-        [116,116,116],
+        [116, 116, 116],
     ]
 
+
 labels_list = []
 
 with open(r'labels.txt', 'r') as fp:
@@ -54,6 +56,7 @@ def label_to_color_image(label):
         raise ValueError("label value too large.")
     return colormap[label]
 
+
 def draw_plot(pred_img, seg):
     fig = plt.figure(figsize=(20, 15))
 
@@ -101,10 +104,12 @@ def sepia(input_img):
     fig = draw_plot(pred_img, seg)
     return fig
 
+
 demo = gr.Interface(fn=sepia,
                     inputs=gr.Image(shape=(400, 600)),
                     outputs=['plot'],
-                    examples=["cityscapes-1.jpg", "cityscapes-2.jpg", "cityscapes-3.jpg", "cityscapes-4.jpg", "cityscapes-5.jpg"],
+                    examples=["cityscapes-1.jpg", "cityscapes-2.jpg", "cityscapes-3.jpg",
+                              "cityscapes-4.jpg", "cityscapes-5.jpg"],
                     allow_flagging='never')