| |
|
|
| """ |
| Convenience script for running IndexTTS2 inference from the command line. |
| |
| Examples |
| -------- |
| Generate Japanese audio with the latest fine-tuned checkpoint: |
| |
| uv run python inference_script.py \ |
| --config checkpoints/config_finetune.yaml \ |
| --speaker vivy.wav \ |
| --text '任務なんてクソくらえ!任務なんてクソくらえよ、ルネ!' \ |
| --output out.wav \ |
| --device cuda:0 |
| |
| You can either pass `--text` directly or use `--text-file` to read the input |
| sentence from disk. All other parameters (tokenizer path, GPT checkpoint, etc.) |
| are taken from the provided config file. |
| """ |
|
|
| from __future__ import annotations |
|
|
| import argparse |
| from pathlib import Path |
| import tempfile |
| from typing import Any, Dict, Optional |
|
|
| from indextts.infer_v2 import IndexTTS2 |
|
|
|
|
| def parse_args() -> argparse.Namespace: |
| parser = argparse.ArgumentParser( |
| description="Run IndexTTS2 inference with configurable speaker prompt and text." |
| ) |
|
|
| parser.add_argument( |
| "--config", |
| type=str, |
| default="checkpoints/config.yaml", |
| help="Path to the YAML config that defines checkpoint/tokenizer paths (default: checkpoints/config.yaml).", |
| ) |
| parser.add_argument( |
| "--model-dir", |
| type=str, |
| default="checkpoints", |
| help="Directory containing weights/tokenizer referenced in the config (default: checkpoints). " |
| "If a file path is supplied, it will be treated as a GPT checkpoint override.", |
| ) |
| parser.add_argument( |
| "--speaker", |
| type=str, |
| required=True, |
| help="Reference speaker audio (wav/mp3/etc.).", |
| ) |
| group = parser.add_mutually_exclusive_group(required=True) |
| group.add_argument( |
| "--text", |
| type=str, |
| help="Text to synthesise.", |
| ) |
| group.add_argument( |
| "--text-file", |
| type=str, |
| help="Path to a UTF-8 text file containing the content to synthesise.", |
| ) |
| parser.add_argument( |
| "--output", |
| type=str, |
| default="output.wav", |
| help="Destination wav file (default: output.wav).", |
| ) |
| parser.add_argument( |
| "--device", |
| type=str, |
| default=None, |
| help="Device string (e.g. cuda:0, cpu). Leave unset for automatic selection.", |
| ) |
| parser.add_argument( |
| "--fp16", |
| action="store_true", |
| help="Use fp16 inference when running on CUDA.", |
| ) |
| parser.add_argument( |
| "--gpt-checkpoint", |
| type=str, |
| default=None, |
| help="Optional path to override the GPT checkpoint referenced in the config.", |
| ) |
| parser.add_argument( |
| "--tokenizer", |
| type=str, |
| default=None, |
| help="Optional path to override the BPE tokenizer referenced in the config.", |
| ) |
| parser.add_argument( |
| "--emo-audio", |
| type=str, |
| default=None, |
| help="Optional emotion reference audio clip.", |
| ) |
| parser.add_argument( |
| "--emo-alpha", |
| type=float, |
| default=1.0, |
| help="Blend factor for the emotion reference audio (default: 1.0).", |
| ) |
| parser.add_argument( |
| "--emo-text", |
| type=str, |
| default=None, |
| help="Text to derive emotion vector from (used when --use-emo-text is supplied).", |
| ) |
| parser.add_argument( |
| "--use-emo-text", |
| action="store_true", |
| help="Derive the emotion vector from text using Qwen emotion model.", |
| ) |
| parser.add_argument( |
| "--max-text-tokens", |
| type=int, |
| default=120, |
| help="Maximum text tokens per segment (default: 120).", |
| ) |
| parser.add_argument( |
| "--top-k", |
| type=int, |
| default=None, |
| help="Sampling top-k (leave unset to use config defaults).", |
| ) |
| parser.add_argument( |
| "--top-p", |
| type=float, |
| default=None, |
| help="Sampling top-p (leave unset to use config defaults).", |
| ) |
| parser.add_argument( |
| "--temperature", |
| type=float, |
| default=None, |
| help="Sampling temperature (leave unset to use config defaults).", |
| ) |
| parser.add_argument( |
| "--num-beams", |
| type=int, |
| default=None, |
| help="Beam search width (leave unset to use config defaults).", |
| ) |
| parser.add_argument( |
| "--interval-silence", |
| type=int, |
| default=200, |
| help="Silence duration (ms) inserted between segments (default: 200).", |
| ) |
| parser.add_argument( |
| "--verbose", |
| action="store_true", |
| help="Print verbose inference logs.", |
| ) |
|
|
| return parser.parse_args() |
|
|
|
|
| def load_text(args: argparse.Namespace) -> str: |
| if args.text is not None: |
| return args.text |
| text_path = Path(args.text_file) |
| if not text_path.exists(): |
| raise FileNotFoundError(f"Text file not found: {text_path}") |
| return text_path.read_text(encoding="utf-8").strip() |
|
|
|
|
| def build_generation_kwargs(args: argparse.Namespace) -> Dict[str, Any]: |
| kwargs: Dict[str, Any] = {} |
| if args.top_k is not None: |
| kwargs["top_k"] = args.top_k |
| if args.top_p is not None: |
| kwargs["top_p"] = args.top_p |
| if args.temperature is not None: |
| kwargs["temperature"] = args.temperature |
| if args.num_beams is not None: |
| kwargs["num_beams"] = args.num_beams |
| return kwargs |
|
|
|
|
| def main() -> None: |
|
|
| import sys |
| sys.argv.append( '--config' ) |
| sys.argv.append( 'checkpoints/config.yaml' ) |
| sys.argv.append( '--text' ) |
| sys.argv.append( '任務なんてクソくらえ!任務なんてクソくらえよ、ルネ!' ) |
| sys.argv.append( '--speaker' ) |
| sys.argv.append( 'vivy.wav' ) |
| sys.argv.append( '--output' ) |
| sys.argv.append( 'out.wav' ) |
| sys.argv.append( '--device' ) |
| sys.argv.append( 'cpu' ) |
|
|
|
|
| args = parse_args() |
| text = load_text(args) |
| generation_kwargs = build_generation_kwargs(args) |
|
|
| |
| cfg_path = Path(args.config) |
| if not cfg_path.exists(): |
| raise FileNotFoundError(f"Config file not found: {cfg_path}") |
|
|
| from omegaconf import OmegaConf |
|
|
| cfg = OmegaConf.load(cfg_path) |
| model_dir_path = Path(args.model_dir).expanduser() |
| gpt_override: Optional[Path] = None |
|
|
| if model_dir_path.is_file(): |
| gpt_override = model_dir_path |
| parent = model_dir_path.parent if model_dir_path.parent != Path("") else cfg_path.parent |
| model_dir_resolved = parent.resolve() |
| else: |
| model_dir_resolved = model_dir_path.resolve() |
|
|
| if args.gpt_checkpoint: |
| gpt_override = Path(args.gpt_checkpoint).expanduser() |
|
|
| if gpt_override is not None: |
| cfg.gpt_checkpoint = str(gpt_override.resolve()) |
|
|
| if args.tokenizer: |
| if "dataset" not in cfg or "bpe_model" not in cfg["dataset"]: |
| raise KeyError("Config does not contain dataset.bpe_model to override.") |
| tokenizer_path = Path(args.tokenizer).expanduser().resolve() |
| cfg.dataset["bpe_model"] = str(tokenizer_path) |
|
|
| |
| tmp_cfg_path: Optional[Path] = None |
| try: |
| with tempfile.NamedTemporaryFile("w", suffix=".yaml", delete=False) as tmp_cfg_file: |
| OmegaConf.save(cfg, tmp_cfg_file.name) |
| tmp_cfg_path = Path(tmp_cfg_file.name) |
|
|
| engine = IndexTTS2( |
| cfg_path=str(tmp_cfg_path), |
| model_dir=str(model_dir_resolved), |
| device=args.device, |
| use_fp16=args.fp16, |
| ) |
|
|
| engine.infer( |
| spk_audio_prompt=args.speaker, |
| text=text, |
| output_path=args.output, |
| emo_audio_prompt=args.emo_audio, |
| emo_alpha=args.emo_alpha, |
| use_emo_text=args.use_emo_text, |
| emo_text=args.emo_text, |
| interval_silence=args.interval_silence, |
| verbose=args.verbose, |
| max_text_tokens_per_segment=args.max_text_tokens, |
| **generation_kwargs, |
| ) |
| print(f"Inference complete. Output saved to {Path(args.output).resolve()}") |
| finally: |
| if tmp_cfg_path is not None: |
| try: |
| tmp_cfg_path.unlink(missing_ok=True) |
| except Exception: |
| pass |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|