Upload 10 files

app.py

@@ -17,24 +17,42 @@ model = TFSegformerForSemanticSegmentation.from_pretrained(
 def ade_palette():
     """ADE20K palette that maps each class to RGB values."""
     return [
-        [255, 255, 255],
         [255, 0, 0],
-        [82, 75, 69],
-        [17, 0, 0],
-        [88, 76, 86],
-        [30, 30, 32],
-        [26, 32, 44],
-        [251, 225, 210],
-        [32, 26, 74],
-        [43, 48, 42],
-        [65, 60, 66],
-        [222, 176, 153],
-        [192, 125, 106],
-        [158, 106, 95],
-        [147, 140, 121],
-        [204, 194, 182],
-        [163, 173, 182],
-        [67, 57, 91],
+        [255, 255, 0],
+        [0, 255, 0],
+        [0, 255, 255],
+        [0, 0, 255],
+        [255, 0, 255],
+        [128, 0, 0],
+        [128, 128, 0],
+        [0, 128, 0],
+        [0, 128, 128],
+        [0, 0, 128],
+        [128, 0, 128],
+        [255, 128, 0],
+        [128, 255, 0],
+        [0, 128, 255],
+        [255, 0, 128],
+        [128, 0, 255],
+        [255, 255, 128],
+        [128, 255, 255],
+        [255, 128, 255],
+        [64, 64, 64],
+        [192, 192, 192],
+        [255, 255, 255],
+        [0, 0, 0],
+        [255, 128, 64],
+        [64, 255, 128],
+        [128, 64, 255],
+        [255, 192, 128],
+        [128, 255, 192],
+        [192, 128, 255],
+        [255, 0, 64],
+        [64, 128, 255],
+        [192, 255, 128],
+        [255, 128, 192],
+        [128, 192, 255],
+        [255, 255, 192],
     ]
 
 labels_list = []
@@ -103,7 +121,7 @@ def sepia(input_img):
 demo = gr.Interface(fn=sepia,
                     inputs=gr.Image(shape=(400, 600)),
                     outputs=['plot'],
-                    examples=["person-1.jpg", "person-2.jpg", "person-3.jpg", "person-4.jpg", "person-5.jpg"],
+                    examples=["sidewalk-1.png", "sidewalk-2.png", "sidewalk-3.png", "sidewalk-4.png", "sidewalk-5.png"],
                     allow_flagging='never')