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GPT_SoVITS.AR.models.t2s_lightning_module import Text2SemanticLightningModule +import GPT_SoVITS.utils as utils i18n = I18nAuto() - - dict_language = { i18n("中文"): "all_zh",#全部按中文识别 i18n("英文"): "en",#全部按英文识别#######不变 @@ -74,7 +73,13 @@ def __delattr__(self, item): def change_sovits_weights(sovits_path): global vq_model, hps + # Patch GPT_SoVITS.utils.HParams to be pickable + # because it conflicts with utils.py in ComfyUI + comfyui_utils = sys.modules['utils'] + sys.modules['utils'] = utils dict_s2 = torch.load(sovits_path, map_location="cpu") + # Restore patch for utils + sys.modules['utils'] = comfyui_utils hps = dict_s2["config"] hps = DictToAttrRecursive(hps) hps.model.semantic_frame_rate = "25hz" diff --git a/nodes.py b/nodes.py index 95fc196..4eaad16 100644 --- a/nodes.py +++ b/nodes.py @@ -72,6 +72,9 @@ def INPUT_TYPES(s): "step": 0.05, "display": "slider" }), + "use_srt":("BOOLEAN",{ + "default": False + }) } } CATEGORY = "AIFSH_GPT_SOVITS" @@ -82,14 +85,18 @@ def INPUT_TYPES(s): def get_tts_wav(self,renfer_audio,refer_srt,refer_language, text,text_language,gpt_weight,sovits_weight, - how_to_cut,top_k,top_p,temperature): + how_to_cut,top_k,top_p,temperature,use_srt): - with open(refer_srt, 'r', encoding="utf-8") as file: - file_content = file.read() prompt_language = dict_language[refer_language] - dot_ = "。" if 'zh' in prompt_language else '.' - prompt_text = f'{dot_}'.join([sub.content for sub in list(SrtPare(file_content))]) - print(f"prompt_text:{prompt_text}") + + prompt_text = None + if use_srt: + with open(refer_srt, 'r', encoding="utf-8") as file: + file_content = file.read() + dot_ = "。" if 'zh' in prompt_language else '.' + prompt_text = f'{dot_}'.join([sub.content for sub in list(SrtPare(file_content))]) + print(f"prompt_text:{prompt_text}") + outfile = os.path.join(out_path, f"{ttime()}_gpt_sovits_tts.wav") gpt_weight = os.path.join(GPT_weight_root, gpt_weight) sovits_weight = os.path.join(SoVITS_weight_root, sovits_weight) diff 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