Spaces:
Running
on
Zero
Running
on
Zero
File size: 4,871 Bytes
aad9d66 bba8617 aad9d66 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 |
"""
Fish Speech TTS/vocals service
"""
import os
import logging
import uuid
import torch
from typing import Optional
import numpy as np
import soundfile as sf
logger = logging.getLogger(__name__)
class FishSpeechService:
"""Service for Fish Speech TTS and vocal synthesis"""
def __init__(self, model_path: str):
"""
Initialize Fish Speech service
Args:
model_path: Path to Fish Speech model files
"""
self.model_path = model_path
self.model = None
self.vocoder = None
self.is_initialized = False
self.device = self._get_device()
logger.info(f"Fish Speech service created with model path: {model_path}")
logger.info(f"Using device: {self.device}")
def _get_device(self):
"""Get compute device (AMD GPU via DirectML or CPU)"""
try:
from utils.amd_gpu import DEFAULT_DEVICE
return DEFAULT_DEVICE
except:
return torch.device("cpu")
def _initialize_model(self):
"""Lazy load the model when first needed"""
if self.is_initialized:
return
try:
logger.info("Initializing Fish Speech model...")
# TODO: Load actual Fish Speech model
# from fish_speech import FishSpeechModel
# self.model = FishSpeechModel.load(self.model_path)
self.is_initialized = True
logger.info("Fish Speech model initialized successfully")
except Exception as e:
logger.error(f"Failed to initialize Fish Speech model: {str(e)}", exc_info=True)
raise RuntimeError(f"Could not load Fish Speech model: {str(e)}")
def synthesize_vocals(
self,
lyrics: str,
duration: int = 30,
sample_rate: int = 44100
) -> str:
"""
Synthesize vocals from lyrics
Args:
lyrics: Lyrics text to sing
duration: Target duration in seconds
sample_rate: Audio sample rate
Returns:
Path to generated vocals file
"""
try:
self._initialize_model()
logger.info(f"Synthesizing vocals: {len(lyrics)} characters")
# TODO: Replace with actual Fish Speech synthesis
# vocals = self.model.synthesize(lyrics, duration=duration, sample_rate=sample_rate)
# Placeholder: Generate silence
vocals = np.zeros(int(duration * sample_rate), dtype=np.float32)
# Save to file
output_dir = os.path.join('outputs', 'vocals')
os.makedirs(output_dir, exist_ok=True)
vocals_id = str(uuid.uuid4())
output_path = os.path.join(output_dir, f"{vocals_id}.wav")
sf.write(output_path, vocals, sample_rate)
logger.info(f"Vocals synthesized: {output_path}")
return output_path
except Exception as e:
logger.error(f"Vocal synthesis failed: {str(e)}", exc_info=True)
raise RuntimeError(f"Failed to synthesize vocals: {str(e)}")
def add_vocals(
self,
music_path: str,
lyrics: str,
duration: int = 30
) -> str:
"""
Add synthesized vocals to music track
Args:
music_path: Path to music audio file
lyrics: Lyrics to sing
duration: Duration in seconds
Returns:
Path to mixed audio file
"""
try:
logger.info(f"Adding vocals to music: {music_path}")
# Load music
music_audio, sr = sf.read(music_path)
# Synthesize vocals
vocals_path = self.synthesize_vocals(lyrics, duration, sr)
vocals_audio, _ = sf.read(vocals_path)
# Mix vocals with music
# Ensure same length
min_len = min(len(music_audio), len(vocals_audio))
mixed = music_audio[:min_len] * 0.7 + vocals_audio[:min_len] * 0.3
# Save mixed audio
output_dir = os.path.join('outputs', 'mixed')
os.makedirs(output_dir, exist_ok=True)
mixed_id = str(uuid.uuid4())
output_path = os.path.join(output_dir, f"{mixed_id}.wav")
sf.write(output_path, mixed, sr)
logger.info(f"Vocals added successfully: {output_path}")
return output_path
except Exception as e:
logger.error(f"Adding vocals failed: {str(e)}", exc_info=True)
raise RuntimeError(f"Failed to add vocals: {str(e)}")
|