Create app.py

app.py

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+from transformers import AutoFeatureExtractor, SegformerForSemanticSegmentation
+import gradio as gr
+import torch
+
+extractor = AutoFeatureExtractor.from_pretrained("salaz055/my_extractor_segmentation_model")
+model = SegformerForSemanticSegmentation.from_pretrained("salaz055/my-segmentation-model")
+
+def classify(im):
+  inputs = extractor(images=im, return_tensors="pt").to("cuda")
+  outputs = model(**inputs)
+  logits = outputs.logits
+  classes = logits[0].detach().cpu().numpy().argmax(axis=0)
+  colors = np.array([[128,0,0], [128,128,0], [0, 0, 128], 	[128,0,128], [0, 0, 0]])
+  return colors[classes]
+  
+interface = gr.Interface(fn = classify,
+                         inputs = gr.Image(type = 'pil'),
+                         outputs = 'image',
+                         title = "Image Segmentation",
+                         description = "Use for semantic image segmentation. Finetuned on sidewalk-semantic") 
+interface.launch()