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Bjornulf_custom_nodes/text_to_speech.py
justumen 66eb5282c2 0.50
2024-10-28 11:32:37 +01:00

166 lines
6.5 KiB
Python

import requests
import numpy as np
import io
import torch
from pydub import AudioSegment
from pydub.playback import play
import urllib.parse
import os
import sys
import random
import re
from typing import Dict, Any, List, Tuple
class Everything(str):
def __ne__(self, __value: object) -> bool:
return False
language_map = {
"ar": "Arabic", "cs": "Czech", "de": "German", "en": "English",
"es": "Spanish", "fr": "French", "hi": "Hindi", "hu": "Hungarian",
"it": "Italian", "ja": "Japanese", "ko": "Korean", "nl": "Dutch",
"pl": "Polish", "pt": "Portuguese", "ru": "Russian", "tr": "Turkish",
"zh-cn": "Chinese"
}
class TextToSpeech:
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
speakers_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "speakers")
speaker_options = [os.path.relpath(os.path.join(root, file), speakers_dir)
for root, _, files in os.walk(speakers_dir)
for file in files if file.endswith(".wav")]
speaker_options = speaker_options or ["No WAV files found"]
return {
"required": {
"text": ("STRING", {"multiline": True}),
"language": (list(language_map.values()), {
"default": language_map["en"],
"display": "dropdown"
}),
"speaker_wav": (speaker_options, {
"default": speaker_options[0],
"display": "dropdown"
}),
"autoplay": ("BOOLEAN", {"default": True}),
"save_audio": ("BOOLEAN", {"default": True}),
"overwrite": ("BOOLEAN", {"default": False}),
"seed": ("INT", {"default": 0}),
},
"optional": {
"connect_to_workflow": (Everything("*"), {"forceInput": True}),
}
}
RETURN_TYPES = ("AUDIO", "STRING", "STRING", "FLOAT")
RETURN_NAMES = ("AUDIO", "audio_path", "audio_full_path", "audio_duration")
FUNCTION = "generate_audio"
CATEGORY = "Bjornulf"
@staticmethod
def get_language_code(language_name: str) -> str:
return next((code for code, name in language_map.items() if name == language_name), "en")
@staticmethod
def sanitize_text(text: str) -> str:
return re.sub(r'[^\w\s-]', '', text).replace(' ', '_')[:50]
def generate_audio(self, text: str, language: str, autoplay: bool, seed: int,
save_audio: bool, overwrite: bool, speaker_wav: str,
connect_to_workflow: Any = None) -> Tuple[Dict[str, Any], str, str, float]:
language_code = self.get_language_code(language)
sanitized_text = self.sanitize_text(text)
save_path = os.path.join("Bjornulf_TTS", language, speaker_wav, f"{sanitized_text}.wav")
full_path = os.path.abspath(save_path)
os.makedirs(os.path.dirname(full_path), exist_ok=True)
if os.path.exists(full_path) and not overwrite:
print(f"Using existing audio file: {full_path}")
audio_data = self.load_audio_file(full_path)
else:
audio_data = self.create_new_audio(text, language_code, speaker_wav, seed)
if save_audio:
self.save_audio_file(audio_data, full_path)
audio_output, _, duration = self.process_audio_data(autoplay, audio_data, full_path if save_audio else None)
return (audio_output, save_path, full_path, duration)
def create_new_audio(self, text: str, language_code: str, speaker_wav: str, seed: int) -> io.BytesIO:
random.seed(seed)
if speaker_wav == "No WAV files found":
print("Error: No WAV files available for text-to-speech.")
return io.BytesIO()
encoded_text = urllib.parse.quote(text)
url = f"http://localhost:8020/tts_stream?language={language_code}&speaker_wav={speaker_wav}&text={encoded_text}"
try:
response = requests.get(url, stream=True)
response.raise_for_status()
audio_data = io.BytesIO()
for chunk in response.iter_content(chunk_size=8192):
audio_data.write(chunk)
audio_data.seek(0)
return audio_data
except requests.RequestException as e:
print(f"Error generating audio: {e}")
return io.BytesIO()
except Exception as e:
print(f"Unexpected error: {e}")
return io.BytesIO()
def play_audio(self, audio: AudioSegment) -> None:
if sys.platform.startswith('win'):
try:
import winsound
winsound.PlaySound(audio.raw_data, winsound.SND_MEMORY)
except Exception as e:
print(f"An error occurred: {e}")
else:
play(audio)
def process_audio_data(self, autoplay: bool, audio_data: io.BytesIO, save_path: str) -> Tuple[Dict[str, Any], str, float]:
try:
audio = AudioSegment.from_mp3(audio_data)
sample_rate = audio.frame_rate
num_channels = audio.channels
audio_np = np.array(audio.get_array_of_samples()).astype(np.float32)
audio_np /= np.iinfo(np.int16).max
audio_np = audio_np.reshape(-1, num_channels).T if num_channels > 1 else audio_np.reshape(1, -1)
audio_tensor = torch.from_numpy(audio_np)
if autoplay:
self.play_audio(audio)
duration = len(audio) / 1000.0 # Convert milliseconds to seconds
return ({"waveform": audio_tensor.unsqueeze(0), "sample_rate": sample_rate}, save_path or "", duration)
except Exception as e:
print(f"Error processing audio data: {e}")
return ({"waveform": torch.zeros(1, 1, 1, dtype=torch.float32), "sample_rate": 22050}, "", 0.0)
def save_audio_file(self, audio_data: io.BytesIO, save_path: str) -> None:
try:
with open(save_path, 'wb') as f:
f.write(audio_data.getvalue())
print(f"Audio saved to: {save_path}")
except Exception as e:
print(f"Error saving audio file: {e}")
def load_audio_file(self, file_path: str) -> io.BytesIO:
try:
with open(file_path, 'rb') as f:
audio_data = io.BytesIO(f.read())
return audio_data
except Exception as e:
print(f"Error loading audio file: {e}")
return io.BytesIO()