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")