Update app.py

app.py

@@ -79,68 +79,10 @@ def denoise(filename, ckpt_path = CHECKPOINT, out = "out.wav"):
 
     return out
 
-#audio = gr.inputs.Audio(label = "Audio to denoise", type = 'filepath')
-#inputs = [audio]
-#outputs = gr.outputs.Audio(label = "Denoised audio", type = 'filepath')
-
-#title = "Speech Denoising in the Waveform Domain with Self-Attention from Nvidia"
-
-#gr.Interface(denoise, inputs, outputs, title=title, enable_queue=True).launch()
-
-
-
-
-demo = gr.Blocks()
-
-mic_transcribe = gr.Interface(
-    fn=denoise,
-    inputs=[
-        gr.inputs.Audio(source="microphone", label="Audio to denoise", type="filepath", optional=True),
-        gr.inputs.Radio(["transcribe", "translate"], label="Task", default="transcribe"),
-        gr.inputs.Checkbox(default=False, label="Return timestamps"),
-    ],
-    
-    outputs=gr.outputs.Audio(label = "Denoised audio", type = 'filepath')
-    
-    layout="horizontal",
-    #theme="huggingface",
-    title="My Demo: Speech enhancement",
-    #description=(
-    #     "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
-    #     f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
-    #     " of arbitrary length."
-    # ),
-    allow_flagging="never",
-)
-#
-mic_transcribe.launch()
-
-# file_transcribe = gr.Interface(
-#     fn=transcribe,
-#     inputs=[
-#         gr.inputs.Audio(source="upload", optional=True, label="Audio file", type="filepath"),
-#         gr.inputs.Radio(["transcribe", "translate"], label="Task", default="transcribe"),
-#         gr.inputs.Checkbox(default=False, label="Return timestamps"),
-#     ],
-#     outputs="text",
-#     layout="horizontal",
-#     theme="huggingface",
-#     title="Whisper Demo: Transcribe Audio",
-#     description=(
-#         "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
-#         f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
-#         " of arbitrary length."
-#     ),
-# #    examples=[
-#  #       ["./example.flac", "transcribe", False],
-#   #      ["./example.flac", "transcribe", True],
-#    # ],
-#     cache_examples=True,
-#     allow_flagging="never",
-# )
-
-# with demo:
-#     gr.TabbedInterface([mic_transcribe, file_transcribe], ["Transcribe Microphone", "Transcribe Audio File"])
-
-# demo.launch(enable_queue=True)
+audio = gr.inputs.Audio(label = "Audio to denoise", type = 'filepath')
+inputs = [audio]
+outputs = gr.outputs.Audio(label = "Denoised audio", type = 'filepath')
 
+title = "Speech Denoising in the Waveform Domain with Self-Attention from Nvidia"
+
+gr.Interface(denoise, inputs, outputs, title=title, enable_queue=True).launch()