mirror of
https://github.com/justUmen/Bjornulf_custom_nodes.git
synced 2026-03-21 12:42:11 -03:00
186 lines
6.0 KiB
Python
186 lines
6.0 KiB
Python
import requests
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import numpy as np
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import io
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import torch
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from pydub import AudioSegment
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from pydub.playback import play
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import urllib.parse
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import os
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import sys
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import random
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import re
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class Everything(str):
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def __ne__(self, __value: object) -> bool:
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return False
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language_map = {
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"ar": "Arabic",
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"cs": "Czech",
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"de": "German",
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"en": "English",
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"es": "Spanish",
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"fr": "French",
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"hi": "Hindi",
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"hu": "Hungarian",
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"it": "Italian",
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"ja": "Japanese",
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"ko": "Korean",
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"nl": "Dutch",
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"pl": "Polish",
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"pt": "Portuguese",
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"ru": "Russian",
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"tr": "Turkish",
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"zh-cn": "Chinese"
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}
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class TextToSpeech:
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@classmethod
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def INPUT_TYPES(cls):
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speakers_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "speakers")
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speaker_options = []
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for root, dirs, files in os.walk(speakers_dir):
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for file in files:
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if file.endswith(".wav"):
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rel_path = os.path.relpath(os.path.join(root, file), speakers_dir)
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speaker_options.append(rel_path)
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if not speaker_options:
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speaker_options.append("No WAV files found")
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language_options = list(language_map.values())
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return {
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"required": {
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"text": ("STRING", {"multiline": True}),
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"language": (language_options, {
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"default": language_map["en"],
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"display": "dropdown"
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}),
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"speaker_wav": (speaker_options, {
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"default": speaker_options[0],
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"display": "dropdown"
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}),
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"autoplay": ("BOOLEAN", {"default": True}),
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"save_audio": ("BOOLEAN", {"default": True}),
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"overwrite": ("BOOLEAN", {"default": False}),
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"seed": ("INT", {"default": 0}),
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},
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"optional": {
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"input": (Everything("*"), {"forceInput": True}),
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}
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}
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RETURN_TYPES = ("AUDIO",)
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FUNCTION = "generate_audio"
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CATEGORY = "Bjornulf"
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@staticmethod
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def get_language_code(language_name):
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for code, name in language_map.items():
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if name == language_name:
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return code
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return "en"
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@staticmethod
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def sanitize_text(text):
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sanitized = re.sub(r'[^\w\s-]', '', text).replace(' ', '_')
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return sanitized[:50]
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def generate_audio(self, text, language, autoplay, seed, save_audio, overwrite, speaker_wav, input=None):
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language_code = self.get_language_code(language)
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sanitized_text = self.sanitize_text(text)
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save_path = os.path.join("Bjornulf_TTS", language, speaker_wav, f"{sanitized_text}.wav")
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os.makedirs(os.path.dirname(save_path), exist_ok=True)
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if os.path.exists(save_path) and not overwrite:
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print(f"Using existing audio file: {save_path}")
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audio_data = self.load_audio_file(save_path)
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else:
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audio_data = self.create_new_audio(text, language_code, speaker_wav, seed)
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if save_audio:
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self.save_audio_file(audio_data, save_path)
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return self.process_audio_data(autoplay, audio_data)
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def create_new_audio(self, text, language_code, speaker_wav, seed):
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random.seed(seed)
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if speaker_wav == "No WAV files found":
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print("Error: No WAV files available for text-to-speech.")
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return io.BytesIO()
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encoded_text = urllib.parse.quote(text)
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url = f"http://localhost:8020/tts_stream?language={language_code}&speaker_wav={speaker_wav}&text={encoded_text}"
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try:
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response = requests.get(url, stream=True)
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response.raise_for_status()
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audio_data = io.BytesIO()
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for chunk in response.iter_content(chunk_size=8192):
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audio_data.write(chunk)
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audio_data.seek(0)
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return audio_data
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except requests.RequestException as e:
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print(f"Error generating audio: {e}")
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return io.BytesIO()
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except Exception as e:
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print(f"Unexpected error: {e}")
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return io.BytesIO()
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def play_audio(self, audio):
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if sys.platform.startswith('win'):
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try:
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import winsound
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winsound.PlaySound(audio, winsound.SND_MEMORY)
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except Exception as e:
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print(f"An error occurred: {e}")
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else:
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play(audio)
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def process_audio_data(self, autoplay, audio_data):
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try:
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audio = AudioSegment.from_mp3(audio_data)
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sample_rate = audio.frame_rate
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num_channels = audio.channels
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audio_np = np.array(audio.get_array_of_samples()).astype(np.float32)
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audio_np /= np.iinfo(np.int16).max
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if num_channels == 1:
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audio_np = audio_np.reshape(1, -1)
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else:
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audio_np = audio_np.reshape(-1, num_channels).T
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audio_tensor = torch.from_numpy(audio_np)
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if autoplay:
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self.play_audio(audio)
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return ({"waveform": audio_tensor.unsqueeze(0), "sample_rate": sample_rate},)
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except Exception as e:
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print(f"Error processing audio data: {e}")
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return ({"waveform": torch.zeros(1, 1, 1, dtype=torch.float32), "sample_rate": 22050},)
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def save_audio_file(self, audio_data, save_path):
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try:
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with open(save_path, 'wb') as f:
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f.write(audio_data.getvalue())
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print(f"Audio saved to: {save_path}")
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except Exception as e:
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print(f"Error saving audio file: {e}")
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def load_audio_file(self, file_path):
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try:
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with open(file_path, 'rb') as f:
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audio_data = io.BytesIO(f.read())
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return audio_data
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except Exception as e:
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print(f"Error loading audio file: {e}")
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return io.BytesIO()
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