| import os | |
| import json | |
| import torch | |
| import asyncio | |
| import librosa | |
| import hashlib | |
| import edge_tts | |
| import gradio as gr | |
| from config import Config | |
| from vc_infer_pipeline import VC | |
| from fairseq import checkpoint_utils | |
| from lib.infer_pack.models import (SynthesizerTrnMs256NSFsid, SynthesizerTrnMs256NSFsid_nono, SynthesizerTrnMs768NSFsid, SynthesizerTrnMs768NSFsid_nono,) | |
| config = Config() | |
| def load_json_file(filepath): | |
| with open(filepath, "r", encoding="utf-8") as f: content = json.load(f) | |
| return content | |
| def file_checksum(file_path): | |
| with open(file_path, 'rb') as f: | |
| file_data = f.read() | |
| return hashlib.md5(file_data).hexdigest() | |
| def get_existing_model_info(category_directory): | |
| model_info_path = os.path.join(category_directory, 'model_info.json') | |
| if os.path.exists(model_info_path): | |
| with open(model_info_path, 'r') as f: return json.load(f) | |
| return None | |
| def generate_model_info_files(): | |
| folder_info = {} | |
| model_directory = "models/" | |
| for category_name in os.listdir(model_directory): | |
| category_directory = os.path.join(model_directory, category_name) | |
| if not os.path.isdir(category_directory): continue | |
| folder_info[category_name] = {"title": category_name, "folder_path": category_name} | |
| existing_model_info = get_existing_model_info(category_directory) | |
| model_info = {} | |
| regenerate_model_info = False | |
| for model_name in os.listdir(category_directory): | |
| model_path = os.path.join(category_directory, model_name) | |
| if not os.path.isdir(model_path): continue | |
| model_data, regenerate = gather_model_info(category_directory, model_name, model_path, existing_model_info) | |
| if model_data is not None: | |
| model_info[model_name] = model_data | |
| regenerate_model_info |= regenerate | |
| if regenerate_model_info: | |
| with open(os.path.join(category_directory, 'model_info.json'), 'w') as f: json.dump(model_info, f, indent=4) | |
| folder_info_path = os.path.join(model_directory, 'folder_info.json') | |
| with open(folder_info_path, 'w') as f: json.dump(folder_info, f, indent=4) | |
| def should_regenerate_model_info(existing_model_info, model_name, pth_checksum, index_checksum): | |
| if existing_model_info is None or model_name not in existing_model_info: return True | |
| return (existing_model_info[model_name]['model_path_checksum'] != pth_checksum or existing_model_info[model_name]['index_path_checksum'] != index_checksum) | |
| def get_model_files(model_path): return [f for f in os.listdir(model_path) if f.endswith('.pth') or f.endswith('.index')] | |
| def gather_model_info(category_directory, model_name, model_path, existing_model_info): | |
| model_files = get_model_files(model_path) | |
| if len(model_files) != 2: return None, False | |
| pth_file = [f for f in model_files if f.endswith('.pth')][0] | |
| index_file = [f for f in model_files if f.endswith('.index')][0] | |
| pth_checksum = file_checksum(os.path.join(model_path, pth_file)) | |
| index_checksum = file_checksum(os.path.join(model_path, index_file)) | |
| regenerate = should_regenerate_model_info(existing_model_info, model_name, pth_checksum, index_checksum) | |
| return {"title": model_name, "model_path": pth_file, "feature_retrieval_library": index_file, "model_path_checksum": pth_checksum, "index_path_checksum": index_checksum}, regenerate | |
| def create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, file_index): | |
| def vc_fn(tts_text, tts_voice): | |
| try: | |
| if len(tts_text) > 100: return None | |
| if tts_text is None or tts_voice is None: return None | |
| asyncio.run(edge_tts.Communicate(tts_text, "-".join(tts_voice.split('-')[:-1])).save("tts.mp3")) | |
| audio, sr = librosa.load("tts.mp3", sr=16000, mono=True) | |
| vc_input = "tts.mp3" | |
| times = [0, 0, 0] | |
| audio_opt = vc.pipeline(hubert_model, net_g, 0, audio, vc_input, times, 0, "pm", file_index, 0.7, if_f0, 3, tgt_sr, 0, 1, version, 0.5, f0_file=None) | |
| return (tgt_sr, audio_opt) | |
| except Exception: return None | |
| return vc_fn | |
| def load_model_parameters(category_folder, character_name, info): | |
| model_index = f"models/{category_folder}/{character_name}/{info['feature_retrieval_library']}" | |
| cpt = torch.load(f"models/{category_folder}/{character_name}/{info['model_path']}", map_location="cpu") | |
| return model_index, cpt | |
| def select_net_g(cpt, version, if_f0): | |
| if version == "v1": | |
| if if_f0 == 1: net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half) | |
| else: net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"]) | |
| elif version == "v2": | |
| if if_f0 == 1: net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half) | |
| else: net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"]) | |
| return net_g | |
| def load_model_and_prepare(cpt, net_g): | |
| del net_g.enc_q | |
| net_g.load_state_dict(cpt["weight"], strict=False) | |
| net_g.eval().to(config.device) | |
| net_g = net_g.half() if config.is_half else net_g.float() | |
| return net_g | |
| def create_and_append_model(models, model_functions, character_name, model_title, version, vc_fn): | |
| models.append((character_name, model_title, version, vc_fn)) | |
| model_functions[character_name] = vc_fn | |
| return models, model_functions | |
| def load_model(): | |
| categories = [] | |
| model_functions = {} | |
| folder_info = load_json_file("models/folder_info.json") | |
| for category_name, category_info in folder_info.items(): | |
| models = [] | |
| models_info = load_json_file(f"models/{category_info['folder_path']}/model_info.json") | |
| for character_name, info in models_info.items(): | |
| model_index, cpt = load_model_parameters(category_info['folder_path'], character_name, info) | |
| net_g = select_net_g(cpt, cpt.get("version", "v1"), cpt.get("f0", 1)) | |
| cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0] | |
| net_g = load_model_and_prepare(cpt, net_g) | |
| vc = VC(cpt["config"][-1], config) | |
| vc_fn = create_vc_fn(info['model_path'], cpt["config"][-1], net_g, vc, cpt.get("f0", 1), cpt.get("version", "v1"), model_index) | |
| models, model_functions = create_and_append_model(models, model_functions, character_name, info['title'], cpt.get("version", "v1"), vc_fn) | |
| categories.append([category_info['title'], category_info['folder_path'], models]) | |
| return categories, model_functions | |
| generate_model_info_files() | |
| css = """ | |
| .gradio-container { font-family: 'IBM Plex Sans', sans-serif; } | |
| footer { visibility: hidden; display: none; } | |
| .center-container { display: flex; flex-direction: column; align-items: center; justify-content: center;} | |
| """ | |
| if __name__ == '__main__': | |
| global hubert_model | |
| models, _, _ = checkpoint_utils.load_model_ensemble_and_task(["hubert_base.pt"], suffix="") | |
| hubert_model = models[0] | |
| hubert_model = hubert_model.to(config.device) | |
| hubert_model = hubert_model.half() if config.is_half else hubert_model.float() | |
| hubert_model.eval() | |
| categories, model_functions = load_model() | |
| tts_voice_list = asyncio.get_event_loop().run_until_complete(edge_tts.list_voices()) | |
| voices = [f"{v['ShortName']}-{v['Gender']}" for v in tts_voice_list] | |
| with gr.Blocks(css=css, title="Demo RVC TTS - Pavloh", theme=gr.themes.Soft(primary_hue="cyan", secondary_hue="blue", radius_size="lg", text_size="lg") | |
| .set(loader_color="#0B0F19", shadow_drop='*shadow_drop_lg', block_border_width="3px")) as pavloh: | |
| gr.HTML(""" | |
| <div class="center-container"> | |
| <div style="display: flex; justify-content: center;"> | |
| <a href="https://github.com/ImPavloh/rvc-tts/blob/main/LICENSE" target="_blank"> | |
| <img src="https://img.shields.io/github/license/impavloh/voiceit?style=for-the-badge&logo=github&logoColor=white" alt="License"> | |
| </a> | |
| <a href="https://github.com/ImPavloh/rvc-tts" target="_blank"> | |
| <img src="https://img.shields.io/badge/repository-%23121011.svg?style=for-the-badge&logo=github&logoColor=white" alt="GitHub"> | |
| </a> | |
| <form action="https://www.paypal.com/donate" method="post" target="_blank"> | |
| <input type="hidden" name="hosted_button_id" value="6FPWP9AWEKSWJ" /> | |
| <input type="image" src="https://img.shields.io/badge/support-%2300457C.svg?style=for-the-badge&logo=paypal&logoColor=white" border="0" name="submit" alt="Donate with PayPal" /> | |
| <img alt="" border="0" src="https://www.paypal.com/es_ES/i/scr/pixel.gif" width="1" height="1" /> | |
| </form> | |
| <a href="https://twitter.com/impavloh" target="_blank"> | |
| <img src="https://img.shields.io/badge/follow-%231DA1F2.svg?style=for-the-badge&logo=twitter&logoColor=white" alt="Twitter"> | |
| </a> | |
| </div> | |
| <div style="display: inline-flex; align-items: center; gap: 0.8rem; font-size: 1.75rem;"> | |
| <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px">🗣️ RVC TTS Demo - <a style="text-decoration: underline;" href="https://twitter.com/impavloh">Pavloh</a></h1> | |
| </div> | |
| <p style="margin-bottom: 10px; font-size: 94%; line-height: 23px;">An AI-Powered Text-to-Speech</p> | |
| <p><b>Try out the <a style="text-decoration: underline;" href="https://github.com/ImPavloh/rvc-tts-discord-bot">RVC Text-to-Speech Discord Bot</a></b></p> | |
| </div> | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| m1 = gr.Dropdown(label="📦 Voice Model", choices=list(model_functions.keys()), allow_custom_value=False, value="Ibai") | |
| t2 = gr.Dropdown(label="⚙️ Voice style and language [Edge-TTS]", choices=voices, allow_custom_value=False, value="es-ES-AlvaroNeural-Male") | |
| t1 = gr.Textbox(label="📝 Text to convert") | |
| c1 = gr.Button("Convert", variant="primary") | |
| a1 = gr.Audio(label="🔉 Converted Text", interactive=False) | |
| def call_selected_model_fn(selected_model, t1, t2): | |
| vc_fn = model_functions[selected_model] | |
| return vc_fn(t1, t2) | |
| c1.click(fn=call_selected_model_fn, inputs=[m1, t1, t2], outputs=[a1]) | |
| gr.HTML(""" | |
| <center> | |
| <p><i> By using this website, you agree to the <a style="text-decoration: underline;" href="https://github.com/ImPavloh/rvc-tts/blob/main/LICENSE">license</a>. </i></p> | |
| </center> | |
| """) | |
| pavloh.queue(concurrency_count=1).launch() |