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| import gradio as gr | |
| import huggingface_hub | |
| import numpy as np | |
| import pandas as pd | |
| import os | |
| import torch | |
| 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 check_outputs_folder(folder_path): | |
| # Check if the folder exists | |
| if os.path.exists(folder_path) and os.path.isdir(folder_path): | |
| # Delete all contents inside the folder | |
| for filename in os.listdir(folder_path): | |
| file_path = os.path.join(folder_path, filename) | |
| try: | |
| if os.path.isfile(file_path) or os.path.islink(file_path): | |
| os.unlink(file_path) # Remove file or link | |
| elif os.path.isdir(file_path): | |
| shutil.rmtree(file_path) # Remove directory | |
| except Exception as e: | |
| print(f'Failed to delete {file_path}. Reason: {e}') | |
| else: | |
| print(f'The folder {folder_path} does not exist.') | |
| def check_for_wav_in_outputs(): | |
| # Define the path to the outputs folder | |
| outputs_folder = './example_1' | |
| # Check if the outputs folder exists | |
| if not os.path.exists(outputs_folder): | |
| return None | |
| # Check if there is a .mp4 file in the outputs folder | |
| mp4_files = [f for f in os.listdir(outputs_folder) if f.endswith('.wav')] | |
| # Return the path to the mp4 file if it exists | |
| if mp4_files: | |
| return os.path.join(outputs_folder, mp4_files[0]) | |
| else: | |
| return None | |
| def infer(text): | |
| # check if 'outputs' dir exists and empty it if necessary | |
| check_outputs_folder('./example_1') | |
| # set hparams | |
| output_dir = 'example_1' ### change this output directory | |
| duration = 30 | |
| num_samples = 1 | |
| 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'] | |
| 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') | |
| wav_file_path = check_for_wav_in_outputs() | |
| print(wav_file_path) | |
| return wav_file_path | |
| with gr.Blocks() as demo: | |
| with gr.Column(): | |
| gr.Markdown("#MusiConGen") | |
| with gr.Row(): | |
| with gr.Column(): | |
| text_in = gr.Textbox() | |
| submit_btn = gr.Button("Submit") | |
| wav_out = gr.Audio(label="Wav Result") | |
| submit_btn.click( | |
| fn = infer, | |
| inputs = [text_in], | |
| outputs = [wav_out] | |
| ) | |
| demo.launch() |