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Retrieval-based-Voice-Conve.../lib/uvr5_pack/lib_v5/model_param_init.py
2023-06-24 15:26:14 +08:00

70 lines
1.6 KiB
Python

import json
import os
import pathlib
default_param = {}
default_param["bins"] = 768
default_param["unstable_bins"] = 9 # training only
default_param["reduction_bins"] = 762 # training only
default_param["sr"] = 44100
default_param["pre_filter_start"] = 757
default_param["pre_filter_stop"] = 768
default_param["band"] = {}
default_param["band"][1] = {
"sr": 11025,
"hl": 128,
"n_fft": 960,
"crop_start": 0,
"crop_stop": 245,
"lpf_start": 61, # inference only
"res_type": "polyphase",
}
default_param["band"][2] = {
"sr": 44100,
"hl": 512,
"n_fft": 1536,
"crop_start": 24,
"crop_stop": 547,
"hpf_start": 81, # inference only
"res_type": "sinc_best",
}
def int_keys(d):
r = {}
for k, v in d:
if k.isdigit():
k = int(k)
r[k] = v
return r
class ModelParameters(object):
def __init__(self, config_path=""):
if ".pth" == pathlib.Path(config_path).suffix:
import zipfile
with zipfile.ZipFile(config_path, "r") as zip:
self.param = json.loads(
zip.read("param.json"), object_pairs_hook=int_keys
)
elif ".json" == pathlib.Path(config_path).suffix:
with open(config_path, "r") as f:
self.param = json.loads(f.read(), object_pairs_hook=int_keys)
else:
self.param = default_param
for k in [
"mid_side",
"mid_side_b",
"mid_side_b2",
"stereo_w",
"stereo_n",
"reverse",
]:
if not k in self.param:
self.param[k] = False