1

app.py

@@ -1,19 +1,13 @@
-import gradio as gr
+from transformers import SegformerFeatureExtractor, SegformerForSemanticSegmentation
 from PIL import Image
 import requests
 
-url1 = "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcR2b2MLoVSTb0tF312bh0HNeFyMPW5w1VV6KZ7yyKw6wx4n7A2uvYaSQkGjsx49yKaKuvU&usqp=CAU"
-url2 = "https://cdn.bizwnews.com/news/photo/202310/67109_71665_5855.jpg"
-url3 = "https://wimg.mk.co.kr/news/cms/202306/28/news-p.v1.20230628.118f551f4481418398049c100db5ef16_P1.jpg"
+feature_extractor = SegformerFeatureExtractor.from_pretrained("nvidia/segformer-b3-finetuned-cityscapes-1024-1024")
+model = SegformerForSemanticSegmentation.from_pretrained("nvidia/segformer-b3-finetuned-cityscapes-1024-1024")
 
-image1 = Image.open(requests.get(url1, stream=True).raw)
-image2 = Image.open(requests.get(url2, stream=True).raw)
-image3 = Image.open(requests.get(url3, stream=True).raw)
-demo = gr.Interface(fn=sepia,
-                    inputs=gr.Image(shape=(400, 600)),
-                    outputs=['plot'],
-                    examples=["image1", "image2", "image3"],
-                    allow_flagging='never')
+url = "http://images.cocodataset.org/val2017/000000039769.jpg"
+image = Image.open(requests.get(url, stream=True).raw)
 
-
-demo.launch()
+inputs = feature_extractor(images=image, return_tensors="pt")
+outputs = model(**inputs)
+logits = outputs.logits  # shape (batch_size, num_labels, height/4, width/4)