add

app.py

@@ -11,29 +11,30 @@ processor = AutoImageProcessor.from_pretrained(MODEL_ID)
 model = AutoModelForSemanticSegmentation.from_pretrained(MODEL_ID)
 
 def ade_palette():
-    """Cityscapes palette that maps each class to RGB values."""
+    # Cityscapes 19-class color map (id2label 순서와 1:1 대응)
     return [
         [128, 64, 128],  # road
         [244, 35, 232],  # sidewalk
         [70, 70, 70],    # building
         [102, 102, 156], # wall
         [190, 153, 153], # fence
-        [0, 128, 0],     # vegetation
+        [153, 153, 153], # pole
+        [250, 170, 30],  # traffic light
+        [220, 220, 0],   # traffic sign
+        [107, 142, 35],  # vegetation
         [152, 251, 152], # terrain
         [70, 130, 180],  # sky
-        [0, 0, 255],     # person
-        [0, 0, 128],     # rider
-        [0, 0, 192],     # car
-        [0, 128, 255],   # truck
-        [0, 255, 0],     # bus
-        [255, 0, 0],     # train
-        [128, 128, 0],   # motorcycle
-        [255, 255, 0],   # bicycle
-        [255, 0, 255],   # other vehicle
-        [128, 0, 0],     # unlabeled
-        [0, 255, 255]    # ground
+        [220, 20, 60],   # person
+        [255, 0, 0],     # rider
+        [0, 0, 142],     # car
+        [0, 0, 70],      # truck
+        [0, 60, 100],    # bus
+        [0, 80, 100],    # train
+        [0, 0, 230],     # motorcycle
+        [119, 11, 32],   # bicycle
     ]
 
+
 labels_list = []
 with open("labels.txt", "r", encoding="utf-8") as fp:
     for line in fp:

labels.txt

@@ -3,6 +3,9 @@ sidewalk
 building
 wall
 fence
+pole
+traffic light
+traffic sign
 vegetation
 terrain
 sky
@@ -14,6 +17,3 @@ bus
 train
 motorcycle
 bicycle
-other vehicle
-unlabeled
-ground