upd3

app.py

@@ -8,10 +8,12 @@ import tensorflow as tf
 from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
 
 feature_extractor = SegformerFeatureExtractor.from_pretrained(
-    "nickmuchi/segformer-b4-finetuned-segments-sidewalk"
+    "nickmuchi/segformer-b4-finetuned-segments-sidewalk",
+    from_pt='True'
 )
 model = TFSegformerForSemanticSegmentation.from_pretrained(
-    "nickmuchi/segformer-b4-finetuned-segments-sidewalk"
+    "nickmuchi/segformer-b4-finetuned-segments-sidewalk",
+    from_pt='True'
 )
 
 def ade_palette():
@@ -62,7 +64,7 @@ with open(r'labels.txt', 'r') as fp:
 
 colormap = np.asarray(ade_palette())
 
-from_pt='True'
+
 def label_to_color_image(label):
     if label.ndim != 2:
         raise ValueError("Expect 2-D input label")
@@ -121,7 +123,7 @@ def sepia(input_img):
 demo = gr.Interface(fn=sepia,
                     inputs=gr.Image(shape=(400, 600)),
                     outputs=['plot'],
-                    examples=["sidewalk-1.jpg", "sidewalk-2.jpg", "sidewalk-2.jpg", "sidewalk-3.jpg"],
+                    examples=["sidewalk-1.jpg", "sidewalk-2.jpg", "sidewalk-3.jpg"],
                     allow_flagging='never')