Update app.py

app.py

@@ -26,10 +26,7 @@ generator = torch.Generator(device)
 def predict(midi_file=None, prompt="", negative_prompt="", audio_length_in_s=10, random_seed=0, controlnet_conditioning_scale=1, num_inference_steps=20, guidance_scale=2.5, guess_mode=False):
  if isinstance(midi_file, _TemporaryFileWrapper):
  midi_file = midi_file.name
- if not isinstance(midi_file, PrettyMIDI):
- midi = PrettyMIDI(midi_file)
- else:
- midi = midi_file
+ midi = PrettyMIDI(midi_file)
  audio = pipe(
  prompt,
  negative_prompt=negative_prompt,
@@ -51,6 +48,9 @@ def synthesize(midi_file=None):
  midi_synth = midi_synth.reshape(midi_synth.shape[0], 1)
  return midi, (SAMPLE_RATE, midi_synth)
 
+def upload(midi_file=None):
+ 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(
  """
@@ -63,9 +63,10 @@ with gr.Blocks(title="🎹 MIDI-AudioLDM", theme=gr.themes.Base(text_size=gr.the
  with gr.Row():
  with gr.Column(variant='panel'):
  midi_synth = gr.Audio(label="synthesized midi")
- midi_file = gr.UploadButton("Upload a MIDI File", file_types=[".mid"], value="S00.mid")
- midi = PrettyMIDI()
- midi_file.upload(synthesize, midi_file, [midi, midi_synth])
+ upload_button = gr.UploadButton("Upload a MIDI File", file_types=[".mid"])
+ midi = gr.File(visible=False, value="S00.mid")
+ midi_file.upload(upload, upload_button, midi)
+ midi_file.upload(synthesize, midi_file, midi)
  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")