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import json |
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import os |
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import shutil |
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import urllib.request |
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import zipfile |
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from argparse import ArgumentParser |
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import gradio as gr |
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from main import song_cover_pipeline, vocal_only_pipeline, vocal_only_pipeline_no_dereverb |
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BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) |
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mdxnet_models_dir = os.path.join(BASE_DIR, 'mdxnet_models') |
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rvc_models_dir = os.path.join(BASE_DIR, 'rvc_models') |
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output_dir = os.path.join(BASE_DIR, 'song_output') |
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def get_current_models(models_dir): |
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models_list = os.listdir(models_dir) |
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items_to_remove = ['hubert_base.pt', 'MODELS.txt', 'public_models.json', 'rmvpe.pt'] |
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return [item for item in models_list if item not in items_to_remove] |
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def update_models_list(): |
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models_l = get_current_models(rvc_models_dir) |
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return gr.Dropdown.update(choices=models_l) |
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def load_public_models(): |
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models_table = [] |
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for model in public_models['voice_models']: |
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if not model['name'] in voice_models: |
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model = [model['name'], model['description'], model['credit'], model['url'], ', '.join(model['tags'])] |
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models_table.append(model) |
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tags = list(public_models['tags'].keys()) |
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return gr.DataFrame.update(value=models_table), gr.CheckboxGroup.update(choices=tags) |
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def extract_zip(extraction_folder, zip_name): |
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os.makedirs(extraction_folder) |
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with zipfile.ZipFile(zip_name, 'r') as zip_ref: |
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zip_ref.extractall(extraction_folder) |
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os.remove(zip_name) |
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index_filepath, model_filepath = None, None |
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for root, dirs, files in os.walk(extraction_folder): |
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for name in files: |
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if name.endswith('.index') and os.stat(os.path.join(root, name)).st_size > 1024 * 100: |
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index_filepath = os.path.join(root, name) |
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if name.endswith('.pth') and os.stat(os.path.join(root, name)).st_size > 1024 * 1024 * 40: |
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model_filepath = os.path.join(root, name) |
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if not model_filepath: |
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raise gr.Error(f'No .pth model file was found in the extracted zip. Please check {extraction_folder}.') |
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os.rename(model_filepath, os.path.join(extraction_folder, os.path.basename(model_filepath))) |
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if index_filepath: |
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os.rename(index_filepath, os.path.join(extraction_folder, os.path.basename(index_filepath))) |
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for filepath in os.listdir(extraction_folder): |
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if os.path.isdir(os.path.join(extraction_folder, filepath)): |
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shutil.rmtree(os.path.join(extraction_folder, filepath)) |
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def download_online_model(url, dir_name, progress=gr.Progress()): |
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try: |
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progress(0, desc=f'[~] Downloading voice model with name {dir_name}...') |
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zip_name = url.split('/')[-1] |
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extraction_folder = os.path.join(rvc_models_dir, dir_name) |
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if os.path.exists(extraction_folder): |
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raise gr.Error(f'Voice model directory {dir_name} already exists! Choose a different name for your voice model.') |
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if 'pixeldrain.com' in url: |
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url = f'https://pixeldrain.com/api/file/{zip_name}' |
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urllib.request.urlretrieve(url, zip_name) |
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progress(0.5, desc='[~] Extracting zip...') |
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extract_zip(extraction_folder, zip_name) |
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return f'[+] {dir_name} Model successfully downloaded!' |
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except Exception as e: |
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raise gr.Error(str(e)) |
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def upload_local_model(zip_path, dir_name, progress=gr.Progress()): |
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try: |
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extraction_folder = os.path.join(rvc_models_dir, dir_name) |
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if os.path.exists(extraction_folder): |
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raise gr.Error(f'Voice model directory {dir_name} already exists! Choose a different name for your voice model.') |
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zip_name = zip_path.name |
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progress(0.5, desc='[~] Extracting zip...') |
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extract_zip(extraction_folder, zip_name) |
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return f'[+] {dir_name} Model successfully uploaded!' |
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except Exception as e: |
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raise gr.Error(str(e)) |
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def filter_models(tags, query): |
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models_table = [] |
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if len(tags) == 0 and len(query) == 0: |
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for model in public_models['voice_models']: |
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models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']]) |
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elif len(tags) > 0 and len(query) > 0: |
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for model in public_models['voice_models']: |
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if all(tag in model['tags'] for tag in tags): |
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model_attributes = f"{model['name']} {model['description']} {model['credit']} {' '.join(model['tags'])}".lower() |
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if query.lower() in model_attributes: |
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models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']]) |
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elif len(tags) > 0: |
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for model in public_models['voice_models']: |
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if all(tag in model['tags'] for tag in tags): |
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models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']]) |
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else: |
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for model in public_models['voice_models']: |
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model_attributes = f"{model['name']} {model['description']} {model['credit']} {' '.join(model['tags'])}".lower() |
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if query.lower() in model_attributes: |
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models_table.append([model['name'], model['description'], model['credit'], model['url'], model['tags']]) |
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return gr.DataFrame.update(value=models_table) |
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def pub_dl_autofill(pub_models, event: gr.SelectData): |
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return gr.Text.update(value=pub_models.loc[event.index[0], 'URL']), gr.Text.update(value=pub_models.loc[event.index[0], 'Model Name']) |
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def swap_visibility(): |
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return gr.update(visible=True), gr.update(visible=False), gr.update(value=''), gr.update(value=None) |
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def process_file_upload(file): |
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return file.name, gr.update(value=file.name) |
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def show_hop_slider(pitch_detection_algo): |
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if pitch_detection_algo == 'mangio-crepe': |
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return gr.update(visible=True) |
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else: |
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return gr.update(visible=False) |
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if __name__ == '__main__': |
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parser = ArgumentParser(description='Generate a AI cover song in the song_output/id directory.', add_help=True) |
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parser.add_argument("--share", action="store_true", dest="share_enabled", default=False, help="Enable sharing") |
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parser.add_argument("--listen", action="store_true", default=False, help="Make the WebUI reachable from your local network.") |
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parser.add_argument('--listen-host', type=str, help='The hostname that the server will use.') |
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parser.add_argument('--listen-port', type=int, help='The listening port that the server will use.') |
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args = parser.parse_args() |
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voice_models = get_current_models(rvc_models_dir) |
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with open(os.path.join(rvc_models_dir, 'public_models.json'), encoding='utf8') as infile: |
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public_models = json.load(infile) |
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with gr.Blocks(title='AICoverGenWebUI') as app: |
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gr.Label('AICoverGen WebUI created with ❤️', show_label=False) |
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with gr.Tab("Generate"): |
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with gr.Accordion('Main Options'): |
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with gr.Row(): |
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with gr.Column(): |
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rvc_model = gr.Dropdown(voice_models, label='Voice Models', info='Models folder "AICoverGen --> rvc_models". After new models are added into this folder, click the refresh button') |
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ref_btn = gr.Button('Refresh Models 🔁', variant='primary') |
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with gr.Column() as yt_link_col: |
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song_input = gr.Text(label='Song input', info='Link to a song on YouTube or full path to a local file. For file upload, click the button below.') |
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show_file_upload_button = gr.Button('Upload file instead') |
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with gr.Column(visible=False) as file_upload_col: |
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local_file = gr.File(label='Audio file') |
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song_input_file = gr.UploadButton('Upload 📂', file_types=['audio'], variant='primary') |
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show_yt_link_button = gr.Button('Paste YouTube link/Path to local file instead') |
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song_input_file.upload(process_file_upload, inputs=[song_input_file], outputs=[local_file, song_input]) |
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with gr.Column(): |
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pitch = gr.Slider(-3, 3, value=0, step=1, label='Pitch Change (Vocals ONLY)', info='Generally, use 1 for male to female conversions and -1 for vice-versa. (Octaves)') |
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pitch_all = gr.Slider(-12, 12, value=0, step=1, label='Overall Pitch Change', info='Changes pitch/key of vocals and instrumentals together. Altering this slightly reduces sound quality. (Semitones)') |
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show_file_upload_button.click(swap_visibility, outputs=[file_upload_col, yt_link_col, song_input, local_file]) |
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show_yt_link_button.click(swap_visibility, outputs=[yt_link_col, file_upload_col, song_input, local_file]) |
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with gr.Accordion('Voice conversion options', open=False): |
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with gr.Row(): |
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index_rate = gr.Slider(0, 1, value=0.5, label='Index Rate', info="Controls how much of the AI voice's accent to keep in the vocals") |
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filter_radius = gr.Slider(0, 7, value=3, step=1, label='Filter radius', info='If >=3: apply median filtering median filtering to the harvested pitch results. Can reduce breathiness') |
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rms_mix_rate = gr.Slider(0, 1, value=0.25, label='RMS mix rate', info="Control how much to mimic the original vocal's loudness (0) or a fixed loudness (1)") |
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protect = gr.Slider(0, 0.5, value=0.33, label='Protect rate', info='Protect voiceless consonants and breath sounds. Set to 0.5 to disable.') |
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with gr.Column(): |
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f0_method = gr.Dropdown(['rmvpe', 'mangio-crepe'], value='rmvpe', label='Pitch detection algorithm', info='Best option is rmvpe (clarity in vocals), then mangio-crepe (smoother vocals)') |
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crepe_hop_length = gr.Slider(32, 320, value=128, step=1, visible=False, label='Crepe hop length', info='Lower values leads to longer conversions and higher risk of voice cracks, but better pitch accuracy.') |
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f0_method.change(show_hop_slider, inputs=f0_method, outputs=crepe_hop_length) |
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keep_files = gr.Checkbox(label='Keep intermediate files', info='Keep all audio files generated in the song_output/id directory, e.g. Isolated Vocals/Instrumentals. Leave unchecked to save space') |
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with gr.Accordion('Audio mixing options', open=False): |
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gr.Markdown('### Volume Change (decibels)') |
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with gr.Row(): |
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main_gain = gr.Slider(-20, 20, value=0, step=1, label='Main Vocals') |
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backup_gain = gr.Slider(-20, 20, value=0, step=1, label='Backup Vocals') |
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inst_gain = gr.Slider(-20, 20, value=0, step=1, label='Music') |
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gr.Markdown('### Reverb Control on AI Vocals') |
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with gr.Row(): |
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reverb_rm_size = gr.Slider(0, 1, value=0.15, label='Room size', info='The larger the room, the longer the reverb time') |
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reverb_wet = gr.Slider(0, 1, value=0.2, label='Wetness level', info='Level of AI vocals with reverb') |
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reverb_dry = gr.Slider(0, 1, value=0.8, label='Dryness level', info='Level of AI vocals without reverb') |
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reverb_damping = gr.Slider(0, 1, value=0.7, label='Damping level', info='Absorption of high frequencies in the reverb') |
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gr.Markdown('### Audio Output Format') |
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output_format = gr.Dropdown(['mp3', 'wav'], value='mp3', label='Output file type', info='mp3: small file size, decent quality. wav: Large file size, best quality') |
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with gr.Row(): |
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clear_btn = gr.ClearButton(value='Clear', components=[song_input, rvc_model, keep_files, local_file]) |
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generate_btn = gr.Button("Generate", variant='primary') |
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ai_cover = gr.Audio(label='AI Cover', show_share_button=False) |
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original_vocals =gr.Audio(label='original_vocals', show_share_button=False) |
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original_instrumentals = gr.Audio(label='original_instrumentals', show_share_button=False) |
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ai_vocals =gr.Audio(label='ai_vocals', show_share_button=False) |
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ref_btn.click(update_models_list, None, outputs=rvc_model) |
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is_webui = gr.Number(value=1, visible=False) |
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generate_btn.click(song_cover_pipeline, |
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inputs=[song_input, rvc_model, pitch, keep_files, is_webui, main_gain, backup_gain, |
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inst_gain, index_rate, filter_radius, rms_mix_rate, f0_method, crepe_hop_length, |
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protect, pitch_all, reverb_rm_size, reverb_wet, reverb_dry, reverb_damping, |
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output_format], |
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outputs=[ai_cover, original_vocals, original_instrumentals, ai_vocals]) |
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clear_btn.click(lambda: [0, 0, 0, 0, 0.5, 3, 0.25, 0.33, 'rmvpe', 128, 0, 0.15, 0.2, 0.8, 0.7, 'mp3', None], |
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outputs=[pitch, main_gain, backup_gain, inst_gain, index_rate, filter_radius, rms_mix_rate, |
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protect, f0_method, crepe_hop_length, pitch_all, reverb_rm_size, reverb_wet, |
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reverb_dry, reverb_damping, output_format, ai_cover]) |
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gr.Label('If you want to modify just voice content...', show_label=False) |
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with gr.Row(): |
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with gr.Column(): |
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rvc_model = gr.Dropdown(voice_models, label='Voice Models', info='Models folder "AICoverGen --> rvc_models". After new models are added into this folder, click the refresh button') |
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ref_btn = gr.Button('Refresh Models 🔁', variant='primary') |
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with gr.Column() as file_upload_col: |
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local_file = gr.File(label='Audio file') |
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song_input_file = gr.UploadButton('Upload 📂', file_types=['audio'], variant='primary') |
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song_input_file.upload(process_file_upload, inputs=[song_input_file], outputs=[local_file, song_input]) |
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with gr.Row(): |
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ai_vocals =gr.Audio(label='ai_vocals', show_share_button=False) |
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ai_vocals_no_dereverb =gr.Audio(label='ai_vocals_no_dereverb', show_share_button=False) |
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generate_btn_vocal_only = gr.Button("Generate Vocal Only", variant='primary') |
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generate_btn_vocal_only_no_dereverb = gr.Button("Generate Vocal Only No Dereverb", variant='primary') |
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ref_btn.click(update_models_list, None, outputs=rvc_model) |
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is_webui = gr.Number(value=1, visible=False) |
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generate_btn_vocal_only.click(vocal_only_pipeline, |
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inputs=[song_input, rvc_model, pitch, is_webui, index_rate, filter_radius, rms_mix_rate, f0_method, crepe_hop_length, |
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protect, pitch_all, reverb_rm_size, reverb_wet, reverb_dry, reverb_damping], |
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outputs=[ai_vocals]) |
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generate_btn_vocal_only_no_dereverb.click(vocal_only_pipeline_no_dereverb, |
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inputs=[song_input, rvc_model, pitch, is_webui, index_rate, filter_radius, rms_mix_rate, f0_method, crepe_hop_length, |
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protect, pitch_all, reverb_rm_size, reverb_wet, reverb_dry, reverb_damping], |
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outputs=[ai_vocals_no_dereverb]) |
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with gr.Tab('Download model'): |
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with gr.Tab('From HuggingFace/Pixeldrain URL'): |
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with gr.Row(): |
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model_zip_link = gr.Text(label='Download link to model', info='Should be a zip file containing a .pth model file and an optional .index file.') |
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model_name = gr.Text(label='Name your model', info='Give your new model a unique name from your other voice models.') |
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with gr.Row(): |
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download_btn = gr.Button('Download 🌐', variant='primary', scale=19) |
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dl_output_message = gr.Text(label='Output Message', interactive=False, scale=20) |
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download_btn.click(download_online_model, inputs=[model_zip_link, model_name], outputs=dl_output_message) |
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gr.Markdown('## Input Examples') |
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gr.Examples( |
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[ |
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['https://huggingface.co/phant0m4r/LiSA/resolve/main/LiSA.zip', 'Lisa'], |
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['https://pixeldrain.com/u/3tJmABXA', 'Gura'], |
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['https://huggingface.co/Kit-Lemonfoot/kitlemonfoot_rvc_models/resolve/main/AZKi%20(Hybrid).zip', 'Azki'] |
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], |
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[model_zip_link, model_name], |
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[], |
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download_online_model, |
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) |
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with gr.Tab('From Public Index'): |
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gr.Markdown('## How to use') |
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gr.Markdown('- Click Initialize public models table') |
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gr.Markdown('- Filter models using tags or search bar') |
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gr.Markdown('- Select a row to autofill the download link and model name') |
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gr.Markdown('- Click Download') |
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with gr.Row(): |
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pub_zip_link = gr.Text(label='Download link to model') |
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pub_model_name = gr.Text(label='Model name') |
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with gr.Row(): |
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download_pub_btn = gr.Button('Download 🌐', variant='primary', scale=19) |
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pub_dl_output_message = gr.Text(label='Output Message', interactive=False, scale=20) |
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filter_tags = gr.CheckboxGroup(value=[], label='Show voice models with tags', choices=[]) |
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search_query = gr.Text(label='Search') |
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load_public_models_button = gr.Button(value='Initialize public models table', variant='primary') |
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public_models_table = gr.DataFrame(value=[], headers=['Model Name', 'Description', 'Credit', 'URL', 'Tags'], label='Available Public Models', interactive=False) |
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public_models_table.select(pub_dl_autofill, inputs=[public_models_table], outputs=[pub_zip_link, pub_model_name]) |
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load_public_models_button.click(load_public_models, outputs=[public_models_table, filter_tags]) |
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search_query.change(filter_models, inputs=[filter_tags, search_query], outputs=public_models_table) |
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filter_tags.change(filter_models, inputs=[filter_tags, search_query], outputs=public_models_table) |
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download_pub_btn.click(download_online_model, inputs=[pub_zip_link, pub_model_name], outputs=pub_dl_output_message) |
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with gr.Tab('Upload model'): |
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gr.Markdown('## Upload locally trained RVC v2 model and index file') |
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gr.Markdown('- Find model file (weights folder) and optional index file (logs/[name] folder)') |
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gr.Markdown('- Compress files into zip file') |
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gr.Markdown('- Upload zip file and give unique name for voice') |
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gr.Markdown('- Click Upload model') |
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with gr.Row(): |
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with gr.Column(): |
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zip_file = gr.File(label='Zip file') |
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local_model_name = gr.Text(label='Model name') |
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with gr.Row(): |
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model_upload_button = gr.Button('Upload model', variant='primary', scale=19) |
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local_upload_output_message = gr.Text(label='Output Message', interactive=False, scale=20) |
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model_upload_button.click(upload_local_model, inputs=[zip_file, local_model_name], outputs=local_upload_output_message) |
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app.launch( |
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share=args.share_enabled, |
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server_name=None if not args.listen else (args.listen_host or '0.0.0.0'), |
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server_port=args.listen_port, |
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) |
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