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import gradio as gr
import numpy as np
import pandas as pd
import os
import torch
# Change the directory
os.chdir('./audiocraft')
from audiocraft.data.audio import audio_write
import audiocraft.models
# download models
huggingface_hub.hf_hub_download(
repo_id='Cyan0731/MusiConGen',
filename='compression_state_dict.bin',
local_dir='./ckpt/musicongen'
)
huggingface_hub.hf_hub_download(
repo_id='Cyan0731/MusiConGen',
filename='state_dict.bin',
local_dir='./ckpt/musicongen'
)
def print_directory_contents(path):
for root, dirs, files in os.walk(path):
level = root.replace(path, '').count(os.sep)
indent = ' ' * 4 * (level)
print(f"{indent}{os.path.basename(root)}/")
subindent = ' ' * 4 * (level + 1)
for f in files:
print(f"{subindent}{f}")
def infer(text):
# set hparams
output_dir = 'example_1' ### change this output directory
duration = 30
num_samples = 5
bs = 1
# load your model
musicgen = audiocraft.models.MusicGen.get_pretrained('./ckpt/musicongen') ### change this path
musicgen.set_generation_params(duration=duration, extend_stride=duration//2, top_k = 250)
chords = ['C G A:min F',
'A:min F C G',
'C F G F',
'C A:min F G',
'D:min G C A:min',
]
descriptions = ["A laid-back blues shuffle with a relaxed tempo, warm guitar tones, and a comfortable groove, perfect for a slow dance or a night in. Instruments: electric guitar, bass, drums."] * num_samples
bpms = [120] * num_samples
meters = [4] * num_samples
wav = []
for i in range(num_samples//bs):
print(f"starting {i} batch...")
temp = musicgen.generate_with_chords_and_beats(descriptions[i*bs:(i+1)*bs],
chords[i*bs:(i+1)*bs],
bpms[i*bs:(i+1)*bs],
meters[i*bs:(i+1)*bs]
)
wav.extend(temp.cpu())
# save and display generated audio
for idx, one_wav in enumerate(wav):
sav_path = os.path.join('./output_samples', output_dir, chords[idx] + "|" + descriptions[idx]).replace(" ", "_")
audio_write(sav_path, one_wav.cpu(), musicgen.sample_rate, strategy='loudness', loudness_compressor=True)
# Print the outputs directory contents
print_directory_contents('./output_samples')
return "done"
with gr.Blocks() as demo:
with gr.Column():
gr.Markdown("#MusiConGen")
with gr.Row():
text_in = gr.Textbox()
submit_btn = gr.Button("Submit")
text_out = gr.Textbox()
submit_btn.click(
fn = infer,
inputs = [text_in],
outputs = [text_out]
)
demo.launch() |