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README.md

@@ -1,8 +1,8 @@
 ---
-title: Non32
+title: Kmc
 emoji: 🚀
-colorFrom: gray
-colorTo: purple
+colorFrom: pink
+colorTo: yellow
 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(
-    "nvidia/segformer-b5-finetuned-cityscapes-1024-1024"
+    "mattmdjaga/segformer_b2_clothes"
 )
 model = TFSegformerForSemanticSegmentation.from_pretrained(
-    "nvidia/segformer-b5-finetuned-cityscapes-1024-1024"
+    "mattmdjaga/segformer_b2_clothes"
 )
 
 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=["cheonggyecheon_stream_in_seoul_city.jpg", "Incheon_stadium.jpg", "Incheon_city.jpg"],
+                    examples=["person-1.jpg", "person-2.jpg", "person-3.jpg", "person-4.jpg", "person-5.jpg"],
                     allow_flagging='never')
 
 

labels.txt

@@ -1,19 +1,18 @@
-road
-sidewalk
-building
-wall
-fence
-pole
-traffic light
-traffic sign
-vegetation
-terrain
-sky
-person
-rider
-car
-truck
-bus
-train
-motorcycle
-bicycle
+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