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README.md

@@ -1,8 +1,8 @@
 ---
-title: Kmc
-emoji: 🚀
-colorFrom: pink
-colorTo: yellow
+title: Non3
+emoji: 🌖
+colorFrom: gray
+colorTo: gray
 sdk: gradio
 sdk_version: 3.44.4
 app_file: app.py

app.py

@@ -8,10 +8,10 @@ import tensorflow as tf
 from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
 
 feature_extractor = SegformerFeatureExtractor.from_pretrained(
-    "mattmdjaga/segformer_b2_clothes"
+    "nvidia/segformer-b5-finetuned-cityscapes-1024-1024"
 )
 model = TFSegformerForSemanticSegmentation.from_pretrained(
-    "mattmdjaga/segformer_b2_clothes"
+    "nvidia/segformer-b5-finetuned-cityscapes-1024-1024"
 )
 
 def ade_palette():
@@ -235,7 +235,7 @@ 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=["cheonggyecheon_stream_in_seoul_city.jpg", "Incheon_stadium.jpeg", "Incheon_city.jpeg"],
                     allow_flagging='never')
 
 

labels.txt

@@ -1,18 +1,19 @@
-Background
-Hat
-Hair
-Sunglasses
-Upper-clothes
-Skirt
-Pants
-Dress
-Belt
-Left-shoe
-Right-shoe
-Face
-Left-leg
-Right-leg
-Left-arm
-Right-arm
-Bag
-Scarf
+road
+sidewalk
+building
+wall
+fence
+pole
+traffic light
+traffic sign
+vegetation
+terrain
+sky
+person
+rider
+car
+truck
+bus
+train
+motorcycle
+bicycle