Update app.py

app.py

@@ -1,17 +1,20 @@
 import gradio as gr
 
-from transformers import SegformerFeatureExtractor, SegformerForSemanticSegmentation
-from PIL import Image
-import requests
 from matplotlib import gridspec
 import matplotlib.pyplot as plt
 import numpy as np
+from PIL import Image
 import tensorflow as tf
+from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
 
 feature_extractor = SegformerFeatureExtractor.from_pretrained(
-    "nielsr/segformer-b0-finetuned-segments-sidewalk")
-model = SegformerForSemanticSegmentation.from_pretrained(
-    "nielsr/segformer-b0-finetuned-segments-sidewalk")
+    "nielsr/segformer-b0-finetuned-segments-sidewalk",
+    from_pt=True
+)
+model = TFSegformerForSemanticSegmentation.from_pretrained(
+    "nielsr/segformer-b0-finetuned-segments-sidewalk",
+    from_pt=True
+)
 
 def ade_palette():
     """ADE20K palette that maps each class to RGB values."""
@@ -117,10 +120,14 @@ def sepia(input_img):
     return fig
 
 demo = gr.Interface(fn=sepia,
+                    title="🚥Sidewalk Segmentation🏃‍️",
+                    description="Image Segmentation for Sidewalks",
                     inputs=gr.Image(),
                     outputs=['plot'],
-                    examples=["Sidewalk_1.jpg", "Sidewalk_2.jpg", "Sidewalk_3.jpg"],
-                    allow_flagging='never')
+                    examples=["Sidewalk_1.jpg", "Sidewalk_2.jpg", "Sidewalk_3.jpg"]],
+                    allow_flagging='never',
+                    theme="gradio/soft",
+                    live=True)
 
 
 demo.launch()