Image_for_segmentation(street)

README.md

@@ -4,7 +4,7 @@ emoji: 🐨
 colorFrom: blue
 colorTo: gray
 sdk: gradio
-sdk_version: 4.2.0
+sdk_version: 3.44.4
 app_file: app.py
 pinned: false
 ---

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-b1-finetuned-cityscapes-1024-1024"
 )
 model = TFSegformerForSemanticSegmentation.from_pretrained(
-    "mattmdjaga/segformer_b2_clothes"
+    "nvidia/segformer-b1-finetuned-cityscapes-1024-1024"
 )
 
 def ade_palette():
@@ -34,7 +34,8 @@ def ade_palette():
         [200, 56, 123],
         [87, 92, 204],
         [120, 56, 123],
-        [45, 78, 123]
+        [45, 78, 123],
+        [0, 0, 0]
     ]
 
 labels_list = []
@@ -103,7 +104,7 @@ 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=["street-1.jpg", "street-2.jpg", "street-3.jpg", "street-4.jpg", "street-5.jpg"],
                     allow_flagging='never')
 
 

labels.txt

@@ -0,0 +1,19 @@
+road
+sidewalk
+building
+wall
+fence
+pole
+traffic light
+traffic sign
+vegetation
+terrain
+sky
+person
+rider
+car
+truck
+bus
+train
+motorcycle
+bicycle