import argparse import os import soundfile as sf from tools.i18n.i18n import I18nAuto from GPT_SoVITS.inference_webui import change_gpt_weights, change_sovits_weights, get_tts_wav i18n = I18nAuto() LANGUAGE_CHOICES = ["中文", "英文", "日文", "韩文", "粤语"] MIXED_LANGUAGE_CHOICES = ["中英混合", "日英混合", "粤英混合", "韩英混合", "多语种混合"] SLICE_METHOD_CHOICES = ["凑四句一切", "凑50字一切", "按标点符号切", "按中文句号。切", "按英文句号.切"] def synthesize(args: argparse.Namespace): # Change model weights change_gpt_weights(gpt_path=args.gpt_path) change_sovits_weights(sovits_path=args.sovits_path) params = { "ref_wav_path": args.ref_audio, "prompt_text": args.ref_text, "prompt_language": i18n(args.ref_language), "text": args.target_text, "text_language": i18n(args.target_language), } # region - optional params if args.slicer: params["how_to_cut"] = i18n(args.slicer) if args.top_k: params["top_k"] = args.top_k if args.top_p: params["top_p"] = args.top_p if args.temperature: params["temperature"] = args.temperature if args.ref_free: params["ref_free"] = args.ref_free if args.speed: params["speed"] = args.speed if args.if_freeze: params["if_freeze"] = args.if_freeze if args.inp_refs: params["inp_refs"] = args.inp_refs if args.sample_steps: params["sample_steps"] = args.sample_steps if args.if_sr: params["if_sr"] = args.if_sr if args.pause_second: params["pause_second"] = args.pause_second # endregion - optional params # Synthesize audio synthesis_result = get_tts_wav(**params) result_list = list(synthesis_result) if result_list: os.makedirs(args.output_path, exist_ok=True) # Create output directory if it doesn't exist output_wav_path = os.path.join(args.output_path, "output.wav") last_sampling_rate, last_audio_data = result_list[-1] sf.write(output_wav_path, last_audio_data, last_sampling_rate) print(f"Audio saved to {output_wav_path}") def build_parser(): parser = argparse.ArgumentParser(description="GPT-SoVITS Command Line Tool") # reference settings parser.add_argument("--ref_audio", required=True, help="Path to the reference audio file") parser.add_argument("--ref_text", required=True, help="Transcript of the reference audio") parser.add_argument("--ref_language", required=True, choices=LANGUAGE_CHOICES, help="Language of the reference audio") # output settings parser.add_argument("--target_text", required=True, help="Text to be synthesized") parser.add_argument("--target_language", required=True, choices=LANGUAGE_CHOICES+MIXED_LANGUAGE_CHOICES, help="Language of the target text") parser.add_argument("--slicer", required=False, choices=SLICE_METHOD_CHOICES, help="Slicer method") parser.add_argument("--output_path", required=True, help="Path to the output directory") # region - inference settings parser.add_argument("--top_k", required=False, type=int, help="Top-k value") parser.add_argument("--top_p", required=False, type=float, help="Top-p value") parser.add_argument("--temperature", required=False, type=float, help="Temperature value") parser.add_argument("--ref_free", required=False, type=bool, help="Reference free value") parser.add_argument("--speed", required=False, type=float, help="Speed value") parser.add_argument("--if_freeze", required=False, type=bool, help="If freeze value") parser.add_argument("--inp_refs", required=False, type=str, help="Input references") parser.add_argument("--sample_steps", required=False, type=int, help="Sample steps value") parser.add_argument("--if_sr", required=False, type=bool, help="If super resolution value") parser.add_argument("--pause_second", required=False, type=float, help="Pause second value") # endregion - inference settings # region - model selection sub = parser.add_subparsers(dest="mode", required=True) # Mode 1: provide model paths directly p_paths = sub.add_parser("paths", help="Use explicit model file paths") p_paths.add_argument("--gpt_path", required=True, help="Path to the GPT model file") p_paths.add_argument("--sovits_path", required=True, help="Path to the SoVITS model file") # Mode 2: select by experiment/version p_sel = sub.add_parser("select", help="Select models by experiment/version") p_sel.add_argument("--exp_name", required=True, help="Experiment name") available_gpt_versions = ["v1", "v2", "v2Pro", "v2ProPlus", "v3", "v4"] p_sel.add_argument("--gpt_version", required=True, choices=available_gpt_versions, help="Version of the GPT model") available_sovits_versions = ["v1", "v2", "v2Pro", "v2ProPlus", "v3", "v4"] p_sel.add_argument("--sovits_version", required=True, choices=available_sovits_versions, help="Version of the SoVITS model") p_sel.add_argument("--gpt_epoch", type=int, help="Epoch of the GPT model") p_sel.add_argument("--sovits_epoch", type=int, help="Epoch of the SoVITS model") # endregion - model selection return parser def get_model_path(args)->argparse.Namespace: """ Get the model path from exp_name, version and epoch Args: args: argparse.Namespace Returns: args: argparse.Namespace """ exist_gpt_path = [] exist_sovits_path = [] def _get_model_dir(model_type, version): if version == "v1": return f"{model_type}_weights" else: return f"{model_type}_weights_{version}" # get all the model paths with the same exp_name for files in os.listdir(_get_model_dir("GPT", args.gpt_version)): if args.exp_name in files and files.endswith(".ckpt"): exist_gpt_path.append(os.path.join(_get_model_dir("GPT", args.gpt_version), files)) for files in os.listdir(_get_model_dir("SoVITS", args.sovits_version)): if args.exp_name in files and files.endswith(".pth"): exist_sovits_path.append(os.path.join(_get_model_dir("SoVITS", args.sovits_version), files)) # get the largest epoch if not specified if args.gpt_epoch: args.gpt_path = [i for i in exist_gpt_path if f"e{args.gpt_epoch}" in i] else: args.gpt_path = sorted(exist_gpt_path)[-1] if args.sovits_epoch: args.sovits_path = [i for i in exist_sovits_path if f"e{args.sovits_epoch}" in i] else: args.sovits_path = sorted(exist_sovits_path)[-1] if not args.gpt_path or not args.sovits_path: raise ValueError("No model found") return args def main(): parser = build_parser() args = parser.parse_args() print(args) if args.mode == "select": args = get_model_path(args) args.target_text = args.target_text.replace("'", "").replace('"', "") synthesize(args) if __name__ == "__main__": main()