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| from io import BytesIO | |
| import requests | |
| from os.path import exists, join | |
| from TTS.utils.synthesizer import Synthesizer | |
| from enum import Enum | |
| from crh_preprocessor.preprocessor import preprocess | |
| from torch import no_grad | |
| class Voices(Enum): | |
| """List of available voices for the model.""" | |
| Arslan = "arslan" | |
| Nuri = "nuri" | |
| Kemal = "kemal" | |
| class TTS: | |
| """ """ | |
| def __init__(self, use_cuda=False) -> None: | |
| """ | |
| Class to setup a text-to-speech engine, from download to model creation. \n | |
| Downloads or uses files from `cache_folder` directory. \n | |
| By default stores in current directory.""" | |
| self.__setup_cache(use_cuda=use_cuda) | |
| def tts(self, text: str, voice: str, output_fp=BytesIO()): | |
| """ | |
| Run a Text-to-Speech engine and output to `output_fp` BytesIO-like object. | |
| - `text` - your model input text. | |
| - `voice` - one of predefined voices from `Voices` enum. | |
| - `output_fp` - file-like object output. Stores in RAM by default. | |
| """ | |
| if voice not in [option.value for option in Voices]: | |
| raise ValueError( | |
| f"Invalid value for voice selected! Please use one of the following values: {', '.join([option.value for option in Voices])}." | |
| ) | |
| text = preprocess(text) | |
| with no_grad(): | |
| wavs = self.synthesizer.tts(text, speaker_name=voice) | |
| self.synthesizer.save_wav(wavs, output_fp) | |
| output_fp.seek(0) | |
| return output_fp, text | |
| def __setup_cache(self, use_cuda=False): | |
| """Downloads models and stores them into `cache_folder`. By default stores in current directory.""" | |
| print("downloading uk/crh/vits-tts") | |
| release_number = "v0.0.1" | |
| model_link = f"https://github.com/robinhad/qirimli-tts/releases/download/{release_number}/model.pth" | |
| config_link = f"https://github.com/robinhad/qirimli-tts/releases/download/{release_number}/config.json" | |
| speakers_link = f"https://github.com/robinhad/qirimli-tts/releases/download/{release_number}/speakers.pth" | |
| cache_folder = "." | |
| model_path = join(cache_folder, "model.pth") | |
| config_path = join(cache_folder, "config.json") | |
| speakers_path = join(cache_folder, "speakers.pth") | |
| self.__download(model_link, model_path) | |
| self.__download(config_link, config_path) | |
| self.__download(speakers_link, speakers_path) | |
| self.synthesizer = Synthesizer( | |
| model_path, config_path, speakers_path, None, None, use_cuda=use_cuda | |
| ) | |
| if self.synthesizer is None: | |
| raise NameError("Model not found") | |
| def __download(self, url, file_name): | |
| """Downloads file from `url` into local `file_name` file.""" | |
| if not exists(file_name): | |
| print(f"Downloading {file_name}") | |
| r = requests.get(url, allow_redirects=True) | |
| with open(file_name, "wb") as file: | |
| file.write(r.content) | |
| else: | |
| print(f"Found {file_name}. Skipping download...") | |