Update app.py

app.py

@@ -48,10 +48,10 @@ def synthesize(midi_file=None):
  midi_synth = midi_synth.reshape(midi_synth.shape[0], 1)
  return (SAMPLE_RATE, midi_synth)
 
-def upload(midi_file=None):
- if isinstance(midi_file, _TemporaryFileWrapper):
- midi_file = midi_file.name
- return midi_file
+# def upload(midi_file=None):
+# if isinstance(midi_file, _TemporaryFileWrapper):
+# midi_file = midi_file.name
+# return midi_file
 
 with gr.Blocks(title="🎹 MIDI-AudioLDM", theme=gr.themes.Base(text_size=gr.themes.sizes.text_md, font=[gr.themes.GoogleFont("Nunito Sans")])) as demo:
  gr.HTML(
@@ -62,13 +62,14 @@ with gr.Blocks(title="🎹 MIDI-AudioLDM", theme=gr.themes.Base(text_size=gr.the
  """
  MIDI-AudioLDM is a MIDI-conditioned text-to-audio model based on the project [AudioLDM](https://huggingface.co/spaces/haoheliu/audioldm-text-to-audio-generation). The model has been conditioned using the ControlNet architecture and has been developed within Hugging Face’s [🧨 Diffusers](https://huggingface.co/docs/diffusers/) framework. Once trained, MIDI-AudioLDM accepts a MIDI file and a text prompt as input and returns an audio file, which is an interpretation of the MIDI based on the given text description. This enables detailed control over different musical aspects such as notes, mood and timbre.
  """)
- upload_button = gr.UploadButton("Upload MIDI file", file_types=[".mid"], value="S00.mid")
+ # upload_button = gr.UploadButton("Upload MIDI file", file_types=[".mid"], value="S00.mid")
  with gr.Row():
  with gr.Column(variant='panel'):
- midi = gr.File(visible=False, value="S00.mid")
+ # midi = gr.File(visible=False, value="S00.mid")
+ midi = gr.File(label="midi file", file_types=[".mid"], value="S00.mid")
  midi_synth = gr.Audio(label="synthesized midi")
- upload_button.upload(upload, upload_button, midi)
- upload_button.upload(synthesize, upload_button, midi_synth)
+ # upload_button.upload(upload, upload_button, midi)
+ midi.upload(synthesize, midi, midi_synth)
  prompt = gr.Textbox(label="prompt", info="Enter a descriptive text prompt to guide the audio generation.")
  with gr.Column(variant='panel'):
  audio = gr.Audio(label="generated audio")