import gradio as gr import spaces import huggingface_hub import numpy as np import pandas as pd import os import shutil 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 = './output_samples/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 @spaces.GPU(duration=80) def infer(prompt_in, chords, duration, bpms): # check if 'outputs' dir exists and empty it if necessary check_outputs_folder('./output_samples/example_1') # set hparams output_dir = 'example_1' ### change this output directory duration = duration 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 = [chords] descriptions = [prompt_in] * num_samples bpms = [bpms] * 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 css=""" #col-container{ max-width: 800px; margin: 0 auto; } #chords-examples button{ font-size: 20px; } """ with gr.Blocks(css=css) as demo: with gr.Column(elem_id="col-container"): gr.Markdown("# MusiConGen") gr.Markdown("## Rhythm and Chord Control for Transformer-Based Text-to-Music Generation") gr.HTML("""
""") with gr.Column(): with gr.Group(): prompt_in = gr.Textbox(label="Music description", value="A smooth acid jazz track with a laid-back groove, silky electric piano, and a cool bass, providing a modern take on jazz. Instruments: electric piano, bass, drums.") with gr.Row(): chords = gr.Textbox(label="Chords progression", value='B:min D F#:min E', scale=1.75) duration = gr.Slider(label="Sample duration", minimum=4, maximum=30, step=1, value=30) bpms = gr.Slider(label="BPMs", minimum=50, maximum=220, step=1, value=120) submit_btn = gr.Button("Submit") wav_out = gr.Audio(label="Wav Result", value="./MusiConGen_default_sample_space_example.wav") with gr.Row(): gr.Examples( label = "Audio description examples", examples = [ ["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."], ["A smooth acid jazz track with a laid-back groove, silky electric piano, and a cool bass, providing a modern take on jazz. Instruments: electric piano, bass, drums."], ["A classic rock n' roll tune with catchy guitar riffs, driving drums, and a pulsating bass line, reminiscent of the golden era of rock. Instruments: electric guitar, bass, drums."], ["A high-energy funk tune with slap bass, rhythmic guitar riffs, and a tight horn section, guaranteed to get you grooving. Instruments: bass, guitar, trumpet, saxophone, drums."], ["A heavy metal onslaught with double kick drum madness, aggressive guitar riffs, and an unrelenting bass, embodying the spirit of metal. Instruments: electric guitar, bass guitar, drums."] ], inputs = [prompt_in] ) gr.Examples( label = "Chords progression examples", elem_id = "chords-examples", examples = ['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', 'D:min7 G:7 C:maj7 C:maj7', 'F G E:min A:min', 'B:min D F#:min E', 'F G E A:min', 'C Bb F C', 'A:min C D F', 'B:min F#:min E:min B:min', 'B:min7 E:9 A:maj7 A:maj7 C#:7 F#:min7', 'F:min G:min Ab Bb', 'A:min G F D:min' ], inputs = [chords], examples_per_page = 16 ) submit_btn.click( fn = infer, inputs = [prompt_in, chords, duration, bpms], outputs = [wav_out] ) demo.launch(show_api=False, show_error=True)