├── README.md
└── text-music generation.py


/README.md:
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1 | # music_generation


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/text-music generation.py:
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 1 | from audiocraft.models import MusicGen
 2 | import streamlit as st 
 3 | import torch 
 4 | import torchaudio
 5 | import os 
 6 | import numpy as np
 7 | import base64
 8 | 
 9 | @st.cache_resource
10 | def load_model():
11 |     model = MusicGen.get_pretrained('facebook/musicgen-small')
12 |     return model
13 | 
14 | def generate_music_tensors(description, duration: int):
15 |     model = load_model()
16 | 
17 |     model.set_generation_params(
18 |         use_sampling=True,
19 |         top_k=250,
20 |         duration=duration
21 |     )
22 | 
23 |     output = model.generate(
24 |         descriptions=[description],
25 |         progress=True,
26 |         return_tokens=True
27 |     )
28 | 
29 |     return output
30 | 
31 | def save_audio(samples, counter):
32 |     sample_rate = 32000
33 |     save_path = "audio_output/"
34 |     
35 |     audio_paths = []
36 |     for idx, audio in enumerate(samples):
37 |         audio_path = os.path.join(save_path, f"music{counter}_{idx}.wav")
38 |         torchaudio.save(audio_path, audio, sample_rate)
39 |         audio_paths.append(audio_path)
40 |     return audio_paths
41 | 
42 | def get_binary_file_downloader_html(bin_files, file_labels):
43 |     hrefs = []
44 |     for bin_file, file_label in zip(bin_files, file_labels):
45 |         with open(bin_file, 'rb') as f:
46 |             data = f.read()
47 |         bin_str = base64.b64encode(data).decode()
48 |         href = f'<a href="data:application/octet-stream;base64,{bin_str}" download="{os.path.basename(bin_file)}">Download {file_label}</a>'
49 |         hrefs.append(href)
50 |     return hrefs
51 | 
52 | st.set_page_config(
53 |     page_icon= "musical_note",
54 |     page_title= "Music Generator"
55 | )
56 | 
57 | counter = 1 
58 | 
59 | def main():
60 |     global counter  
61 |     st.title("Text to Music Generator using Python")
62 | 
63 |     with st.sidebar:
64 |         st.subheader("Available Song Genres:")
65 |         st.write("- Pop")
66 |         st.write("- Rock")
67 |         st.write("- Jazz")
68 |         st.write("- Classical")
69 |         st.write("- Hip-hop")
70 |         st.write("- Electronic")
71 |         st.write("- Country")
72 | 
73 |     st.markdown("---")  # Separator between sidebar and main content
74 | 
75 |     st.write("Please enter a sentence or lyrics describing the mood or style of music you want to generate.")
76 |     text_area = st.text_area("Enter your sentence or lyrics")
77 | 
78 |     time_slider = st.slider("Select time duration (In Seconds)", 0, 20, 10)
79 | 
80 |     if st.button("Generate Music"):
81 |         if text_area and time_slider:
82 |             st.json({
83 |                 'Your Description': text_area,
84 |                 'Selected Time Duration (in Seconds)': time_slider
85 |             })
86 | 
87 |             st.subheader("Generated Music")
88 |             music_tensors = generate_music_tensors(text_area, time_slider)
89 |             audio_filepaths = save_audio(music_tensors, counter)
90 |             audio_file_labels = [f"Audio {i+1}" for i in range(len(music_tensors))]
91 |             for i in range(len(music_tensors)):
92 |                 st.audio(open(audio_filepaths[i], 'rb').read(), format='audio/wav')
93 |                 st.markdown(get_binary_file_downloader_html([audio_filepaths[i]], [audio_file_labels[i]])[0], unsafe_allow_html=True)
94 | 
95 |             counter += 1  
96 | 
97 | if _name_ == "_main_":
98 |     main()


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