Update app.py

app.py

@@ -10,32 +10,26 @@ def predict(image):
     preds = [{"score": round(pred["score"], 4), "label": pred["label"]} for pred in preds]
     return preds
 
-description = """
-"""
-
 def format_output(output):
-    # Format the JSON output for better display
     formatted_output = ""
-    for i, pred in enumerate(output):
-        formatted_output += f"{i}: {{\n"
-        formatted_output += f"  score: {pred['score']},\n"
-        formatted_output += f"  label: {pred['label']}\n"
-        formatted_output += "}\n"
+    for idx, pred in enumerate(output):
+        formatted_output += f"{idx}: Score: {pred['score']}, Label: {pred['label']}\n"
     return formatted_output
 
-# Create the Gradio interface
+description = """
+"""
+
 iface = gr.Interface(
     fn=predict,
     inputs=[
-        gr.inputs.Image(label="Image to classify", type="pil"),
+        gr.components.Image(label="Image to classify", type="pil"),
     ],
     outputs=gr.outputs.JSON(),
     title="Image Classifier",
     description=description
 )
 
-# Set the post-processing hook to format the output
-iface.interface_output_postprocessing = format_output
+# Apply custom formatting to the JSON output
+iface.outputs[0].format = format_output
 
-# Launch the interface
 iface.launch()