Update app.py

app.py

@@ -1,11 +1,10 @@
 import gradio as gr
-
-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
+from PIL import Image
+from transformers import SegformerImageProcessor, TFSegformerForSemanticSegmentation
+import matplotlib.pyplot as plt
+from matplotlib import gridspec
 
 feature_extractor = SegformerFeatureExtractor.from_pretrained(
     "nvidia/segformer-b0-finetuned-cityscapes-1024-1024"
@@ -17,25 +16,24 @@ model = TFSegformerForSemanticSegmentation.from_pretrained(
 def ade_palette():
     """ADE20K palette that maps each class to RGB values."""
     return [
-        [204, 87, 92],
-        [112, 185, 212],
-        [45, 189, 106],
-        [234, 123, 67],
-        [78, 56, 123],
-        [210, 32, 89],
-        [90, 180, 56],
-        [155, 102, 200],
-        [33, 147, 176],
-        [255, 183, 76],
-        [67, 123, 89],
-        [190, 60, 45],
-        [134, 112, 200],
-        [56, 45, 189],
-        [200, 56, 123],
-        [87, 92, 204],
-        [120, 56, 123],
-        [45, 78, 123],
-        [156, 200, 56],
+        [255, 0, 0],
+        [255, 187, 0],
+        [255, 228, 0],
+        [29, 219, 22],
+        [178, 204, 255],
+        [1, 0, 255], 
+        [165, 102, 255],
+        [217, 65, 197],
+        [116, 116, 116],
+        [204, 114, 61],
+        [206, 242, 121],
+        [61, 183, 204],
+        [94, 94, 94],
+        [196, 183, 59],
+        [246, 246, 246],
+        [209, 178, 255],
+        [0, 87, 102],
+        [153, 0, 76]
     ]
 
 labels_list = []
@@ -102,7 +100,7 @@ def sepia(input_img):
     return fig
 
 demo = gr.Interface(fn=sepia,
-                    inputs=gr.Image(shape=(400, 600)),
+                    inputs=gr.Image(shape=(800, 1200)),
                     outputs=['plot'],
                     examples=["citiscapes-1.jpeg", "citiscapes-2.jpeg"],
                     allow_flagging='never')