import os import sys JSON_AS_ASCII = False MAX_CONTENT_LENGTH = 5242880 # Flask debug mode DEBUG = False # Server port PORT = 7860 # Absolute path of vits-simple-api ABS_PATH = os.path.join(os.path.dirname(os.path.realpath(sys.argv[0]))) # Upload path UPLOAD_FOLDER = ABS_PATH + "/upload" # Cahce path CACHE_PATH = ABS_PATH + "/cache" # If CLEAN_INTERVAL_SECONDS <= 0, the cleaning task will not be executed. CLEAN_INTERVAL_SECONDS = 3600 # save audio to CACHE_PATH SAVE_AUDIO = False # zh ja ko en... If it is empty, it will be read based on the text_cleaners specified in the config.json. LANGUAGE_AUTOMATIC_DETECT = [] # Set to True to enable API Key authentication API_KEY_ENABLED = False # API_KEY is required for authentication API_KEY = "api-key" # logging_level:DEBUG/INFO/WARNING/ERROR/CRITICAL LOGGING_LEVEL = "DEBUG" # Language identification library. Optional fastlid, langid LANGUAGE_IDENTIFICATION_LIBRARY = "langid" # To use the english_cleaner, you need to install espeak and provide the path of libespeak-ng.dll as input here. # If ESPEAK_LIBRARY is set to empty, it will be read from the environment variable. # For windows : "C:/Program Files/eSpeak NG/libespeak-ng.dll" ESPEAK_LIBRARY = "" # Fill in the model path here MODEL_LIST = [ # VITS [ABS_PATH + "/Model/Nene_Nanami_Rong_Tang/1374_epochs.pth", ABS_PATH + "/Model/Nene_Nanami_Rong_Tang/config.json"], [ABS_PATH + "/Model/vctk/pretrained_vctk.pth", ABS_PATH + "/Model/vctk/vctk_base.json"], [ABS_PATH + "/Model/paimon/paimon6k_390000.pth", ABS_PATH + "/Model/paimon/paimon6k.json"], [ABS_PATH + "/Model/vits_chinese/vits_bert_model.pth", ABS_PATH + "/Model/vits_chinese/bert_vits.json"], [ABS_PATH + "/Model/Bishojo_Mangekyo/generator_mangekyo.pth", ABS_PATH + "/Model/Bishojo_Mangekyo/config_mangekyo.json"], [ABS_PATH + "/Model/Cantonese/model.pth", ABS_PATH + "/Model/Cantonese/config.json"], [ABS_PATH + "/Model/shanghainese/2796_epochs.pth", ABS_PATH + "/Model/shanghainese/config.json"], [ABS_PATH + "/Model/genshin/G_953000.pth", ABS_PATH + "/Model/genshin/config.json"], # HuBert-VITS (Need to configure HUBERT_SOFT_MODEL) [ABS_PATH + "/Model/louise/360_epochs.pth", ABS_PATH + "/Model/louise/config.json"], # W2V2-VITS (Need to configure DIMENSIONAL_EMOTION_NPY) [ABS_PATH + "/Model/w2v2-vits/1026_epochs.pth", ABS_PATH + "/Model/w2v2-vits/config.json"], ] # hubert-vits: hubert soft model HUBERT_SOFT_MODEL = ABS_PATH + "/Model/hubert-soft-0d54a1f4.pt" # w2v2-vits: Dimensional emotion npy file # load single npy: ABS_PATH+"/all_emotions.npy # load mutiple npy: [ABS_PATH + "/emotions1.npy", ABS_PATH + "/emotions2.npy"] # load mutiple npy from folder: ABS_PATH + "/Model/npy" DIMENSIONAL_EMOTION_NPY = ABS_PATH + "/Model/npy" # w2v2-vits: Need to have both `model.onnx` and `model.yaml` files in the same path. DIMENSIONAL_EMOTION_MODEL = ABS_PATH + "/Model/model.yaml" """ Default parameter """ ID = 0 FORMAT = "wav" LANG = "AUTO" LENGTH = 1 NOISE = 0.33 NOISEW = 0.4 # 长文本分段阈值,max<=0表示不分段. # Batch processing threshold. Text will not be processed in batches if max<=0 MAX = 50