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