Create app.py

app.py

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+import streamlit as st
+import librosa
+import soundfile as sf
+import os
+import time
+import numpy as np
+
+# Set the home directory path for moonarch
+home_directory = os.getcwd()
+
+# Function to ensure directory exists
+def ensure_directory_exists(directory):
+    if not os.path.exists(directory):
+        os.makedirs(directory)
+
+# Function to process the audio
+def process_audio(file_path, choice):
+    # Ensure to navigate to the home directory first
+    os.chdir(home_directory)
+    
+    file_name_without_ext = os.path.splitext(os.path.basename(file_path))[0]
+    
+    
+    
+    if choice == 'Basic Split':
+        output_dir = os.path.join('basic_splits', file_name_without_ext)
+        ensure_directory_exists(output_dir)
+        os.chdir('basic_splits')
+        from moonarch_basic import BasicSplitter
+        splitter = BasicSplitter(file_path)
+        splitter.run()
+        st.write("Basic split process completed.")
+        os.chdir(home_directory)
+        ensure_directory_exists(os.path.join('vocal_remover', file_name_without_ext))
+        os.chdir('vocal_remover')
+        from moonarch_vocal_remover import VocalRemover
+        music_sep = VocalRemover(file_path)
+        music_sep.run()
+        st.write("Vocal remover process completed.")
+        os.chdir(home_directory)
+        return [
+            os.path.join('basic_splits', file_name_without_ext, 'vocals.wav'),
+            os.path.join('vocal_remover', file_name_without_ext, 'accompaniment.wav'),
+            os.path.join('basic_splits', file_name_without_ext, 'bass.wav'),
+            os.path.join('basic_splits', file_name_without_ext, 'drums.wav')
+        ]
+    
+    
+# Streamlit app
+st.title('Monarch Music Analysis: Basic Splits')
+
+task_choice = st.selectbox('Choose a task', ['Basic Split'])
+
+uploaded_file = st.file_uploader('Upload an audio file', type=['mp3', 'wav'])
+
+if uploaded_file is not None:
+    # Save uploaded file to a temporary location
+    audio_file_path = os.path.join(home_directory, f'{uploaded_file.name}')
+    with open(audio_file_path, 'wb') as f:
+        f.write(uploaded_file.getbuffer())
+    
+    y, sr = librosa.load(audio_file_path, sr=None)  # sr=None to use the native sample rate
+
+    if st.button('Start'):
+        progress_bar = st.progress(0)
+        
+        # Simulate progress bar for processing
+        for percent_complete in range(100):
+            time.sleep(0.01)
+            progress_bar.progress(percent_complete + 1)
+
+        output_files = process_audio(audio_file_path, task_choice)
+        
+        st.success('Audio processed successfully!')
+
+        for file in output_files:
+            file_name = os.path.basename(file)
+            if 'vocals.wav' in file:
+                st.write('Vocal')
+            elif 'accompaniment.wav' in file:
+                st.write('Music')
+            elif 'bass.wav' in file:
+                st.write('Bass')
+            elif 'drums.wav' in file:
+                st.write('Drums')
+            elif 'piano.wav' in file:
+                st.write('Piano')
+            elif 'strings_or_pads.wav' in file:
+                st.write('Strings or Pads')
+               
+            st.audio(file)
+            with open(file, 'rb') as f:
+                new_file_name = 'music.wav' if file_name == 'accompaniment.wav' else ('strings_or_pads.wav' if file_name == 'other.wav' else file_name)
+                st.download_button(label=f'Download {new_file_name}', data=f, file_name=new_file_name)