Update app.py

app.py

@@ -1,16 +1,23 @@
+import gradio as gr
 from transformers import AutoFeatureExtractor, SwinForImageClassification
 from PIL import Image
 import requests
 
-url = "http://images.cocodataset.org/val2017/000000039769.jpg"
-image = Image.open(requests.get(url, stream=True).raw)
-
 feature_extractor = AutoFeatureExtractor.from_pretrained("microsoft/swin-small-patch4-window7-224")
 model = SwinForImageClassification.from_pretrained("microsoft/swin-small-patch4-window7-224")
 
-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()
-print("Predicted class:", model.config.id2label[predicted_class_idx])
+def classify_image(url):
+    image = Image.open(requests.get(url, stream=True).raw)
+    inputs = feature_extractor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    return model.config.id2label[predicted_class_idx]
+
+examples = [
+    ["http://images.cocodataset.org/val2017/000000039769.jpg"],
+]
+
+iface = gr.Interface(fn=classify_image, inputs="text", outputs="text", examples=examples)
+iface.launch()
+