Update app.py

app.py

@@ -10,14 +10,14 @@ pipe = pipeline(
   chunk_length_s=30,
   device=device,
 )
+ 
 
-ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
-sample = ds[0]["audio"]
-
-prediction = pipe(sample.copy(), batch_size=8)["text"]
-" Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel."
+gradio_app = gr.Interface(
+    predict,
+    inputs=gr.Audio(label="Select hot dog candidate", sources=['upload', 'webcam'], type="pil"),
+    outputs=[gr. Audio(label="Processed Image"), gr.Label(label="Result", num_top_classes=2)],
+    title="Hot Dog? Or Not?",
+)
 
-# we can also return timestamps for the predictions
-prediction = pipe(sample.copy(), batch_size=8, return_timestamps=True)["chunks"]
-[{'text': ' Mr. Quilter is the apostle of the middle classes and we are glad to welcome his gospel.',
-  'timestamp': (0.0, 5.44)}]
+if __name__ == "__main__":
+    gradio_app.launch()