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| import streamlit as st | |
| import torch | |
| import torchaudio | |
| import os | |
| import numpy as np | |
| import base64 | |
| from audiocraft.models import MusicGen | |
| # Before | |
| batch_size = 64 | |
| # After | |
| batch_size = 32 | |
| torch.cuda.empty_cache() | |
| genres = ["Pop", "Rock", "Jazz", "Electronic", "Hip-Hop", "Classical", "Lofi", "Chillpop"] | |
| def load_model(): | |
| model = MusicGen.get_pretrained('facebook/musicgen-small') | |
| return model | |
| def generate_music_tensors(description, duration: int): | |
| model = load_model() | |
| model.set_generation_params( | |
| use_sampling=True, | |
| top_k=250, | |
| duration=duration | |
| ) | |
| with st.spinner("Generating Music..."): | |
| output = model.generate( | |
| descriptions=description, | |
| progress=True, | |
| return_tokens=True | |
| ) | |
| st.success("Music Generation Complete!") | |
| return output | |
| def save_audio(samples: torch.Tensor): | |
| sample_rate = 30000 | |
| save_path = "audio_output" | |
| assert samples.dim() == 2 or samples.dim() == 3 | |
| samples = samples.detach().cpu() | |
| if samples.dim() == 2: | |
| samples = samples[None, ...] | |
| for idx, audio in enumerate(samples): | |
| audio_path = os.path.join(save_path, f"audio_{idx}.wav") | |
| torchaudio.save(audio_path, audio, sample_rate) | |
| def get_binary_file_downloader_html(bin_file, file_label='File'): | |
| with open(bin_file, 'rb') as f: | |
| data = f.read() | |
| bin_str = base64.b64encode(data).decode() | |
| href = f'<a href="data:application/octet-stream;base64,{bin_str}" download="{os.path.basename(bin_file)}">Download {file_label}</a>' | |
| return href | |
| st.set_page_config( | |
| page_icon= "musical_note", | |
| page_title= "Music Gen" | |
| ) | |
| def main(): | |
| st.title("🎧 AI Composer Medium-Model 🎧") | |
| st.subheader("Craft your perfect melody!") | |
| bpm = st.number_input("Enter Speed in BPM", min_value=60) | |
| text_area = st.text_area('Ex : 80s rock song with guitar and drums') | |
| st.text('') | |
| # Dropdown for genres | |
| selected_genre = st.selectbox("Select Genre", genres) | |
| st.subheader("2. Select time duration (In Seconds)") | |
| time_slider = st.slider("Select time duration (In Seconds)", 0, 30, 10) | |
| # mood = st.selectbox("Select Mood (Optional)", ["Happy", "Sad", "Angry", "Relaxed", "Energetic"], None) | |
| # instrument = st.selectbox("Select Instrument (Optional)", ["Piano", "Guitar", "Flute", "Violin", "Drums"], None) | |
| # tempo = st.selectbox("Select Tempo (Optional)", ["Slow", "Moderate", "Fast"], None) | |
| # melody = st.text_input("Enter Melody or Chord Progression (Optional)", "e.g: C D:min G:7 C, Twinkle Twinkle Little Star") | |
| if st.button('Let\'s Generate 🎶'): | |
| st.text('\n\n') | |
| st.subheader("Generated Music") | |
| # Generate audio | |
| description = text_area # Initialize description with text_area | |
| if selected_genre: | |
| description += f" {selected_genre}" | |
| st.empty() # Hide the selected_genre selectbox after selecting one option | |
| if bpm: | |
| description += f" {bpm} BPM" | |
| # if mood: | |
| # description += f" {mood}" | |
| # st.empty() # Hide the mood selectbox after selecting one option | |
| # if instrument: | |
| # description += f" {instrument}" | |
| # st.empty() # Hide the instrument selectbox after selecting one option | |
| # if tempo: | |
| # description += f" {tempo}" | |
| # st.empty() # Hide the tempo selectbox after selecting one option | |
| # if melody: | |
| # description += f" {melody}" | |
| # Clear CUDA memory cache before generating music | |
| torch.cuda.empty_cache() | |
| music_tensors = generate_music_tensors(description, time_slider) | |
| # Only play the full audio for index 0 | |
| idx = 0 | |
| music_tensor = music_tensors[idx] | |
| save_audio(music_tensor) | |
| audio_filepath = f'/audio_output/audio_{idx}.wav' | |
| audio_file = open(audio_filepath, 'rb') | |
| audio_bytes = audio_file.read() | |
| # Play the full audio | |
| st.audio(audio_bytes, format='audio/wav') | |
| st.markdown(get_binary_file_downloader_html(audio_filepath, f'Audio_{idx}'), unsafe_allow_html=True) | |
| if __name__ == "__main__": | |
| main() |