Update app.py

app.py

@@ -56,32 +56,21 @@ def gradio_predict(url, threshold):
     tags, error = predict_tags(url, threshold)
     if error:
         return error, None
-    # Return tags, and the image as a PIL object
     image = load_image_from_url(url)
     return "\n".join([f"{tag}: {score:.2f}" for tag, score in tags]), image
 
-
 demo = gr.Interface(
     fn=gradio_predict,
     inputs=[
-        gr.Textbox(label="Image URL", value="https://d2q1sfov6ca7my.cloudfront.net/eyJidWNrZXQiOiJoaWNjdXAtaW1hZ2UtaG9zdGluZyIsImtleSI6ImhpY2N1cC1wcm9kdWN0cy9GQVFZTFkyNzFGLmpwZWciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjI1NjAsImhlaWdodCI6Mzg0MCwiZml0IjoiY292ZXIifX19?v=1748968367"),
+        gr.Textbox(label="Image URL"),
         gr.Slider(0, 1, value=0.5, step=0.01, label="Threshold"),
     ],
     outputs=[
         gr.Textbox(label="Tags"),
-        gr.Image(label="Preview", type="url"),
+        gr.Image(label="Preview", type="pil"),
     ],
     title="Image Tagging with ViT",
     description="Paste an image URL and get predicted tags using thelabel/240903-image-tagging model.",
-    examples=[
-        [
-            "https://d2q1sfov6ca7my.cloudfront.net/eyJidWNrZXQiOiJoaWNjdXAtaW1hZ2UtaG9zdGluZyIsImtleSI6ImhpY2N1cC1wcm9kdWN0cy9GQVFZTFkyNzFGLmpwZWciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjI1NjAsImhlaWdodCI6Mzg0MCwiZml0IjoiY292ZXIifX19?v=1748968367", 0.5
-        ],
-        [
-            "https://d2q1sfov6ca7my.cloudfront.net/eyJidWNrZXQiOiJoaWNjdXAtaW1hZ2UtaG9zdGluZyIsImtleSI6ImhpY2N1cC1wcm9kdWN0cy9ON01aQkpUMDlFLmpwZWciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjI1NjAsImhlaWdodCI6Mzg0MCwiZml0IjoiY292ZXIifX19?v=1748968367", 0.5
-        ]
-    ]
 )
-
 if __name__ == "__main__":
     demo.launch()