done!

app.py

@@ -0,0 +1,23 @@
+from transformers import SegformerFeatureExtractor, SegformerForImageClassification
+from PIL import Image
+import requests
+
+import gradio as gr
+
+
+
+def seg(image):
+    feature_extractor = SegformerFeatureExtractor.from_pretrained("nvidia/mit-b0")
+    model = SegformerForImageClassification.from_pretrained("nvidia/mit-b0")
+    print(model)
+    
+    inputs = feature_extractor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits
+    # model predicts one of the 1000 ImageNet classes
+    predicted_class_idx = logits.argmax(-1).item()
+    return model.config.id2label[predicted_class_idx]
+
+    
+iface = gr.Interface(fn=seg, inputs=gr.inputs.Image(type='pil'), outputs='label')
+iface.launch()

requirements.txt

@@ -0,0 +1,4 @@
+transformers
+torch
+timm
+datasets