#!flask/bin/python # installation on Ubuntu 18: # apt install python3-pip # pip3 install --upgrade pip # pip3 --version # pip3 install TTS # find /usr -name server.py # wget -O /usr/local/lib/python3.6/dist-packages/TTS/server/server.py https://botcompany.de/serve/1032538 # tts-server -h import argparse import io import json import os import sys from pathlib import Path from typing import Union from flask import Flask, render_template, request, send_file from TTS.config import load_config from TTS.utils.manage import ModelManager from TTS.utils.synthesizer import Synthesizer print("tts-server patched from https://code.botcompany.de/1032538") def create_argparser(): def convert_boolean(x): return x.lower() in ["true", "1", "yes"] parser = argparse.ArgumentParser() parser.add_argument( "--list_models", type=convert_boolean, nargs="?", const=True, default=False, help="list available pre-trained tts and vocoder models.", ) parser.add_argument( "--model_name", type=str, default="tts_models/en/ljspeech/tacotron2-DDC", help="Name of one of the pre-trained tts models in format //", ) parser.add_argument("--vocoder_name", type=str, default=None, help="name of one of the released vocoder models.") # Args for running custom models parser.add_argument("--config_path", default=None, type=str, help="Path to model config file.") parser.add_argument( "--model_path", type=str, default=None, help="Path to model file.", ) parser.add_argument( "--vocoder_path", type=str, help="Path to vocoder model file. If it is not defined, model uses GL as vocoder. Please make sure that you installed vocoder library before (WaveRNN).", default=None, ) parser.add_argument("--vocoder_config_path", type=str, help="Path to vocoder model config file.", default=None) parser.add_argument("--speakers_file_path", type=str, help="JSON file for multi-speaker model.", default=None) parser.add_argument("--port", type=int, default=5002, help="port to listen on.") parser.add_argument("--use_cuda", type=convert_boolean, default=False, help="true to use CUDA.") parser.add_argument("--debug", type=convert_boolean, default=False, help="true to enable Flask debug mode.") parser.add_argument("--show_details", type=convert_boolean, default=False, help="Generate model detail page.") return parser # parse the args args = create_argparser().parse_args() path = Path(__file__).parent / "../.models.json" manager = ModelManager(path) if args.list_models: manager.list_models() sys.exit() # update in-use models to the specified released models. model_path = None config_path = None speakers_file_path = None vocoder_path = None vocoder_config_path = None # CASE1: list pre-trained TTS models if args.list_models: manager.list_models() sys.exit() # CASE2: load pre-trained model paths if args.model_name is not None and not args.model_path: model_path, config_path, model_item = manager.download_model(args.model_name) args.vocoder_name = model_item["default_vocoder"] if args.vocoder_name is None else args.vocoder_name if args.vocoder_name is not None and not args.vocoder_path: vocoder_path, vocoder_config_path, _ = manager.download_model(args.vocoder_name) # CASE3: set custome model paths if args.model_path is not None: model_path = args.model_path config_path = args.config_path speakers_file_path = args.speakers_file_path if args.vocoder_path is not None: vocoder_path = args.vocoder_path vocoder_config_path = args.vocoder_config_path # load models synthesizer = Synthesizer( model_path, config_path, speakers_file_path, vocoder_path, vocoder_config_path, use_cuda=args.use_cuda ) use_multi_speaker = hasattr(synthesizer.tts_model, "speaker_manager") and synthesizer.tts_model.num_speakers > 1 speaker_manager = getattr(synthesizer.tts_model, "speaker_manager", None) # TODO: set this from SpeakerManager use_gst = synthesizer.tts_config.get("use_gst", False) app = Flask(__name__) def style_wav_uri_to_dict(style_wav: str) -> Union[str, dict]: """Transform an uri style_wav, in either a string (path to wav file to be use for style transfer) or a dict (gst tokens/values to be use for styling) Args: style_wav (str): uri Returns: Union[str, dict]: path to file (str) or gst style (dict) """ if style_wav: if os.path.isfile(style_wav) and style_wav.endswith(".wav"): return style_wav # style_wav is a .wav file located on the server style_wav = json.loads(style_wav) return style_wav # style_wav is a gst dictionary with {token1_id : token1_weigth, ...} return None @app.route("/") def index(): return render_template( "index.html", show_details=args.show_details, use_multi_speaker=use_multi_speaker, speaker_ids=speaker_manager.speaker_ids if speaker_manager is not None else None, use_gst=use_gst, ) @app.route("/details") def details(): model_config = load_config(args.tts_config) if args.vocoder_config is not None and os.path.isfile(args.vocoder_config): vocoder_config = load_config(args.vocoder_config) else: vocoder_config = None return render_template( "details.html", show_details=args.show_details, model_config=model_config, vocoder_config=vocoder_config, args=args.__dict__, ) @app.route("/api/tts", methods=["GET", "POST"]) def tts(): text = request.values.get("text") speaker_idx = request.values.get("speaker_id", "") style_wav = request.values.get("style_wav", "") style_wav = style_wav_uri_to_dict(style_wav) print(" > Model input: {}".format(text)) wavs = synthesizer.tts(text, speaker_idx=speaker_idx, style_wav=style_wav) out = io.BytesIO() synthesizer.save_wav(wavs, out) return send_file(out, mimetype="audio/wav") def main(): app.run(debug=args.debug, port=args.port) if __name__ == "__main__": main()