Upload 2 files

app.py

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+import streamlit as st
+import torch
+from unidecode import unidecode
+from musc.model import PretrainedModel
+from unidecode import unidecode
+import os
+import sys
+import torch
+import json
+#from yt_dlp import YoutubeDL
+sys.path.append('MUSC_violin')
+from MUSC_violin import musc
+
+# Function to transcribe the WAV file and generate the MIDI file
+def transcribe_and_generate_midi(wav_file_path, model, batch_size=32, postprocessing='spotify'):
+    midi, _, title = model.transcribe_wav(wav_file_path, batch_size=batch_size, postprocessing=postprocessing)
+
+    # Write the MIDI file
+    midi_file_name = unidecode(title) + '.mid'
+    midi.write(midi_file_name)
+
+    return midi_file_name, title
+
+# Set up the Pretrained Model
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+model = PretrainedModel(instrument='violin').to(device)
+
+# Streamlit UI
+st.title("Violin to MIDI Converter")
+
+uploaded_file = st.file_uploader("Upload your WAV file", type=["wav"])
+
+if uploaded_file is not None:
+    st.write("File Uploaded Successfully!")
+    st.audio(uploaded_file, format='audio/wav')
+
+    if st.button("Convert to MIDI"):
+        try:
+            midi_file_name, title = transcribe_and_generate_midi(uploaded_file, model)
+            st.success(f"MIDI file generated successfully: {midi_file_name}")
+            st.audio(midi_file_name, format='audio/midi', label='Download MIDI')
+        except Exception as e:
+            st.error(f"Error: {str(e)}")
+else:
+    st.info("Please upload a WAV file to convert to MIDI.")

requirement.txt

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+yt-dlp
+mir_eval
+pretty_midi
+unidecode
+streamlit