mirror of
https://github.com/Anjok07/ultimatevocalremovergui.git
synced 2024-11-24 07:20:10 +01:00
423 lines
17 KiB
Python
423 lines
17 KiB
Python
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import json
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def get_vr_download_list(list):
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with open("lib_v5/filelists/download_lists/vr_download_list.txt", "r") as f:
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text=f.read().splitlines()
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list = text
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return list
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def get_mdx_download_list(list):
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with open("lib_v5/filelists/download_lists/mdx_download_list.txt", "r") as f:
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text=f.read().splitlines()
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list = text
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return list
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def get_demucs_download_list(list):
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with open("lib_v5/filelists/download_lists/demucs_download_list.txt", "r") as f:
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text=f.read().splitlines()
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list = text
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return list
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def get_mdx_demucs_en_list(list):
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with open("lib_v5/filelists/ensemble_list/mdx_demuc_en_list.txt", "r") as f:
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text=f.read().splitlines()
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list = text
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return list
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def get_vr_en_list(list):
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with open("lib_v5/filelists/ensemble_list/vr_en_list.txt", "r") as f:
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text=f.read().splitlines()
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list = text
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return list
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def get_download_links(links, downloads=''):
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f = open(f"lib_v5/filelists/download_lists/download_links.json")
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download_links = json.load(f)
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if downloads == 'Demucs v3: mdx':
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url_1 = download_links['Demucs_v3_mdx_url_1']
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url_2 = download_links['Demucs_v3_mdx_url_2']
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url_3 = download_links['Demucs_v3_mdx_url_3']
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url_4 = download_links['Demucs_v3_mdx_url_4']
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url_5 = download_links['Demucs_v3_mdx_url_5']
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links = url_1, url_2, url_3, url_4, url_5
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if downloads == 'Demucs v3: mdx_q':
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url_1 = download_links['Demucs_v3_mdx_q_url_1']
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url_2 = download_links['Demucs_v3_mdx_q_url_2']
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url_3 = download_links['Demucs_v3_mdx_q_url_3']
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url_4 = download_links['Demucs_v3_mdx_q_url_4']
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url_5 = download_links['Demucs_v3_mdx_q_url_5']
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links = url_1, url_2, url_3, url_4, url_5
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if downloads == 'Demucs v3: mdx_extra':
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url_1 = download_links['Demucs_v3_mdx_extra_url_1']
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url_2 = download_links['Demucs_v3_mdx_extra_url_1']
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url_3 = download_links['Demucs_v3_mdx_extra_url_1']
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url_4 = download_links['Demucs_v3_mdx_extra_url_1']
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url_5 = download_links['Demucs_v3_mdx_extra_url_1']
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links = url_1, url_2, url_3, url_4, url_5
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if downloads == 'Demucs v3: mdx_extra_q':
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url_1 = download_links['Demucs_v3_mdx_extra_q_url_1']
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url_2 = download_links['Demucs_v3_mdx_extra_q_url_2']
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url_3 = download_links['Demucs_v3_mdx_extra_q_url_3']
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url_4 = download_links['Demucs_v3_mdx_extra_q_url_4']
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url_5 = download_links['Demucs_v3_mdx_extra_q_url_5']
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links = url_1, url_2, url_3, url_4, url_5
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if downloads == 'Demucs v3: UVR Models':
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url_1 = download_links['Demucs_v3_UVR_url_1']
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url_2 = download_links['Demucs_v3_UVR_url_2']
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url_3 = download_links['Demucs_v3_UVR_url_3']
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url_4 = download_links['Demucs_v3_UVR_url_4']
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url_5 = download_links['Demucs_v3_UVR_url_5']
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links = url_1, url_2, url_3, url_4, url_5
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if downloads == 'Demucs v2: demucs':
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url_1 = download_links['Demucs_v2_demucs_url_1']
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links = url_1
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if downloads == 'Demucs v2: demucs_extra':
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url_1 = download_links['Demucs_v2_demucs_extra_url_1']
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links = url_1
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if downloads == 'Demucs v2: demucs48_hq':
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url_1 = download_links['Demucs_v2_demucs48_hq_url_1']
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links = url_1
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if downloads == 'Demucs v2: tasnet':
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url_1 = download_links['Demucs_v2_tasnet_url_1']
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links = url_1
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if downloads == 'Demucs v2: tasnet_extra':
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url_1 = download_links['Demucs_v2_tasnet_extra_url_1']
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links = url_1
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if downloads == 'Demucs v2: demucs_unittest':
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url_1 = download_links['Demucs_v2_demucs_unittest_url_1']
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links = url_1
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if downloads == 'Demucs v1: demucs':
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url_1 = download_links['Demucs_v1_demucs_url_1']
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links = url_1
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if downloads == 'Demucs v1: demucs_extra':
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url_1 = download_links['Demucs_v1_demucs_extra_url_1']
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links = url_1
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if downloads == 'Demucs v1: light':
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url_1 = download_links['Demucs_v1_light_url_1']
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links = url_1
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if downloads == 'Demucs v1: light_extra':
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url_1 = download_links['Demucs_v1_light_extra_url_1']
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links = url_1
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if downloads == 'Demucs v1: tasnet':
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url_1 = download_links['Demucs_v1_tasnet_url_1']
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links = url_1
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if downloads == 'Demucs v1: tasnet_extra':
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url_1 = download_links['Demucs_v1_tasnet_extra_url_1']
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links = url_1
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if downloads == 'model_repo':
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url_1 = download_links['model_repo_url_1']
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links = url_1
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if downloads == 'single_model_repo':
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url_1 = download_links['single_model_repo_url_1']
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links = url_1
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if downloads == 'exclusive':
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url_1 = download_links['exclusive_url_1']
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url_2 = download_links['exclusive_url_2']
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links = url_1, url_2, url_3
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if downloads == 'refresh':
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url_1 = download_links['refresh_url_1']
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url_2 = download_links['refresh_url_2']
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url_3 = download_links['refresh_url_3']
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links = url_1, url_2, url_3
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if downloads == 'app_patch':
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url_1 = download_links['app_patch']
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links = url_1
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return links
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def provide_model_param_hash(model_hash):
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#v5 Models
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if model_hash == '47939caf0cfe52a0e81442b85b971dfd':
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model_params_set=str('lib_v5/modelparams/4band_44100.json')
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param_name=str('4band_44100')
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elif model_hash == '4e4ecb9764c50a8c414fee6e10395bbe':
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model_params_set=str('lib_v5/modelparams/4band_v2.json')
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param_name=str('4band_v2')
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elif model_hash == 'e60a1e84803ce4efc0a6551206cc4b71':
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model_params_set=str('lib_v5/modelparams/4band_44100.json')
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param_name=str('4band_44100')
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elif model_hash == 'a82f14e75892e55e994376edbf0c8435':
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model_params_set=str('lib_v5/modelparams/4band_44100.json')
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param_name=str('4band_44100')
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elif model_hash == '6dd9eaa6f0420af9f1d403aaafa4cc06':
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model_params_set=str('lib_v5/modelparams/4band_v2_sn.json')
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param_name=str('4band_v2_sn')
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elif model_hash == '5c7bbca45a187e81abbbd351606164e5':
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model_params_set=str('lib_v5/modelparams/3band_44100_msb2.json')
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param_name=str('3band_44100_msb2')
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elif model_hash == 'd6b2cb685a058a091e5e7098192d3233':
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model_params_set=str('lib_v5/modelparams/3band_44100_msb2.json')
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param_name=str('3band_44100_msb2')
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elif model_hash == 'c1b9f38170a7c90e96f027992eb7c62b':
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model_params_set=str('lib_v5/modelparams/4band_44100.json')
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param_name=str('4band_44100')
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elif model_hash == 'c3448ec923fa0edf3d03a19e633faa53':
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model_params_set=str('lib_v5/modelparams/4band_44100.json')
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param_name=str('4band_44100')
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elif model_hash == '68aa2c8093d0080704b200d140f59e54':
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model_params_set=str('lib_v5/modelparams/3band_44100.json')
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param_name=str('3band_44100.json')
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elif model_hash == 'fdc83be5b798e4bd29fe00fe6600e147':
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model_params_set=str('lib_v5/modelparams/3band_44100_mid.json')
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param_name=str('3band_44100_mid.json')
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elif model_hash == '2ce34bc92fd57f55db16b7a4def3d745':
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model_params_set=str('lib_v5/modelparams/3band_44100_mid.json')
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param_name=str('3band_44100_mid.json')
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elif model_hash == '52fdca89576f06cf4340b74a4730ee5f':
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model_params_set=str('lib_v5/modelparams/4band_44100.json')
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param_name=str('4band_44100.json')
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elif model_hash == '41191165b05d38fc77f072fa9e8e8a30':
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model_params_set=str('lib_v5/modelparams/4band_44100.json')
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param_name=str('4band_44100.json')
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elif model_hash == '89e83b511ad474592689e562d5b1f80e':
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model_params_set=str('lib_v5/modelparams/2band_32000.json')
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param_name=str('2band_32000.json')
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elif model_hash == '0b954da81d453b716b114d6d7c95177f':
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model_params_set=str('lib_v5/modelparams/2band_32000.json')
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param_name=str('2band_32000.json')
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#v4 Models
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elif model_hash == '6a00461c51c2920fd68937d4609ed6c8':
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model_params_set=str('lib_v5/modelparams/1band_sr16000_hl512.json')
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param_name=str('1band_sr16000_hl512')
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elif model_hash == '0ab504864d20f1bd378fe9c81ef37140':
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model_params_set=str('lib_v5/modelparams/1band_sr32000_hl512.json')
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param_name=str('1band_sr32000_hl512')
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elif model_hash == '7dd21065bf91c10f7fccb57d7d83b07f':
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model_params_set=str('lib_v5/modelparams/1band_sr32000_hl512.json')
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param_name=str('1band_sr32000_hl512')
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elif model_hash == '80ab74d65e515caa3622728d2de07d23':
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model_params_set=str('lib_v5/modelparams/1band_sr32000_hl512.json')
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param_name=str('1band_sr32000_hl512')
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elif model_hash == 'edc115e7fc523245062200c00caa847f':
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model_params_set=str('lib_v5/modelparams/1band_sr33075_hl384.json')
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param_name=str('1band_sr33075_hl384')
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elif model_hash == '28063e9f6ab5b341c5f6d3c67f2045b7':
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model_params_set=str('lib_v5/modelparams/1band_sr33075_hl384.json')
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param_name=str('1band_sr33075_hl384')
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elif model_hash == 'b58090534c52cbc3e9b5104bad666ef2':
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model_params_set=str('lib_v5/modelparams/1band_sr44100_hl512.json')
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param_name=str('1band_sr44100_hl512')
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elif model_hash == '0cdab9947f1b0928705f518f3c78ea8f':
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model_params_set=str('lib_v5/modelparams/1band_sr44100_hl512.json')
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param_name=str('1band_sr44100_hl512')
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elif model_hash == 'ae702fed0238afb5346db8356fe25f13':
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model_params_set=str('lib_v5/modelparams/1band_sr44100_hl1024.json')
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param_name=str('1band_sr44100_hl1024')
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else:
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try:
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with open(f"lib_v5/filelists/model_cache/vr_param_cache/{model_hash}.txt", "r") as f:
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name = f.read()
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model_params_set=str(f'lib_v5/modelparams/{name}')
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param_name=str(name)
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('using text of hash worked')
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except:
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model_params_set=str('Not Found Using Hash')
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param_name=str('Not Found Using Hash')
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model_params = model_params_set, param_name
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return model_params
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def provide_model_param_name(ModelName):
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#1 Band
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if '1band_sr16000_hl512' in ModelName:
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model_params_set=str('lib_v5/modelparams/1band_sr16000_hl512.json')
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param_name=str('1band_sr16000_hl512')
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elif '1band_sr32000_hl512' in ModelName:
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model_params_set=str('lib_v5/modelparams/1band_sr32000_hl512.json')
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param_name=str('1band_sr32000_hl512')
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elif '1band_sr33075_hl384' in ModelName:
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model_params_set=str('lib_v5/modelparams/1band_sr33075_hl384.json')
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param_name=str('1band_sr33075_hl384')
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elif '1band_sr44100_hl256' in ModelName:
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model_params_set=str('lib_v5/modelparams/1band_sr44100_hl256.json')
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param_name=str('1band_sr44100_hl256')
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elif '1band_sr44100_hl512' in ModelName:
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model_params_set=str('lib_v5/modelparams/1band_sr44100_hl512.json')
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param_name=str('1band_sr44100_hl512')
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elif '1band_sr44100_hl1024' in ModelName:
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model_params_set=str('lib_v5/modelparams/1band_sr44100_hl1024.json')
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param_name=str('1band_sr44100_hl1024')
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#2 Band
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elif '2band_44100_lofi' in ModelName:
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model_params_set=str('lib_v5/modelparams/2band_44100_lofi.json')
|
||
|
|
param_name=str('2band_44100_lofi')
|
||
|
|
|
||
|
|
#3 Band
|
||
|
|
|
||
|
|
elif '3band_44100_mid' in ModelName:
|
||
|
|
model_params_set=str('lib_v5/modelparams/3band_44100_mid.json')
|
||
|
|
param_name=str('3band_44100_mid')
|
||
|
|
elif '3band_44100_msb2' in ModelName:
|
||
|
|
model_params_set=str('lib_v5/modelparams/3band_44100_msb2.json')
|
||
|
|
param_name=str('3band_44100_msb2')
|
||
|
|
|
||
|
|
#4 Band
|
||
|
|
|
||
|
|
elif '4band_44100_msb' in ModelName:
|
||
|
|
model_params_set=str('lib_v5/modelparams/4band_44100_msb.json')
|
||
|
|
param_name=str('4band_44100_msb')
|
||
|
|
elif '4band_44100_msb2' in ModelName:
|
||
|
|
model_params_set=str('lib_v5/modelparams/4band_44100_msb2.json')
|
||
|
|
param_name=str('4band_44100_msb2')
|
||
|
|
elif '4band_44100_reverse' in ModelName:
|
||
|
|
model_params_set=str('lib_v5/modelparams/4band_44100_reverse.json')
|
||
|
|
param_name=str('4band_44100_reverse')
|
||
|
|
elif 'tmodelparam' in ModelName:
|
||
|
|
model_params_set=str('lib_v5/modelparams/tmodelparam.json')
|
||
|
|
param_name=str('User Model Param Set')
|
||
|
|
else:
|
||
|
|
model_params_set=str('Not Found Using Name')
|
||
|
|
param_name=str('Not Found Using Name')
|
||
|
|
|
||
|
|
model_params = model_params_set, param_name
|
||
|
|
|
||
|
|
return model_params
|
||
|
|
|
||
|
|
def provide_mdx_model_param_name(modelhash):
|
||
|
|
with open("lib_v5/filelists/hashes/mdx_original_hashes.txt", "r") as f:
|
||
|
|
mdx_original=f.read()
|
||
|
|
with open("lib_v5/filelists/hashes/mdx_new_hashes.txt", "r") as f:
|
||
|
|
mdx_new=f.read()
|
||
|
|
with open("lib_v5/filelists/hashes/mdx_new_inst_hashes.txt", "r") as f:
|
||
|
|
mdx_new_inst=f.read()
|
||
|
|
|
||
|
|
if modelhash in mdx_original:
|
||
|
|
MDX_modeltype = 'mdx_original'
|
||
|
|
elif modelhash in mdx_new:
|
||
|
|
MDX_modeltype = 'mdx_new'
|
||
|
|
elif modelhash in mdx_new_inst:
|
||
|
|
MDX_modeltype = 'mdx_new_inst'
|
||
|
|
else:
|
||
|
|
MDX_modeltype = 'None'
|
||
|
|
|
||
|
|
if MDX_modeltype == 'mdx_original':
|
||
|
|
modeltype = 'v'
|
||
|
|
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||
|
|
stemset_n = '(Vocals)'
|
||
|
|
compensate = 1.03597672895
|
||
|
|
source_val = 3
|
||
|
|
n_fft_scale_set=6144
|
||
|
|
dim_f_set=2048
|
||
|
|
elif MDX_modeltype == 'mdx_new':
|
||
|
|
modeltype = 'v'
|
||
|
|
noise_pro = 'MDX-NET_Noise_Profile_17_kHz'
|
||
|
|
stemset_n = '(Vocals)'
|
||
|
|
compensate = 1.08
|
||
|
|
source_val = 3
|
||
|
|
n_fft_scale_set=7680
|
||
|
|
dim_f_set=3072
|
||
|
|
elif MDX_modeltype == 'mdx_new_inst':
|
||
|
|
modeltype = 'v'
|
||
|
|
noise_pro = 'MDX-NET_Noise_Profile_17_kHz'
|
||
|
|
stemset_n = '(Instrumental)'
|
||
|
|
compensate = 1.08
|
||
|
|
source_val = 3
|
||
|
|
n_fft_scale_set=7680
|
||
|
|
dim_f_set=3072
|
||
|
|
elif modelhash == '6f7eefc2e6b9d819ba88dc0578056ca5':
|
||
|
|
modeltype = 'o'
|
||
|
|
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
|
||
|
|
stemset_n = '(Other)'
|
||
|
|
compensate = 1.03597672895
|
||
|
|
source_val = 2
|
||
|
|
n_fft_scale_set=8192
|
||
|
|
dim_f_set=2048
|
||
|
|
elif modelhash == '72a27258a69b2381b60523a50982e9f1':
|
||
|
|
modeltype = 'd'
|
||
|
|
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
|
||
|
|
stemset_n = '(Drums)'
|
||
|
|
compensate = 1.03597672895
|
||
|
|
source_val = 1
|
||
|
|
n_fft_scale_set=4096
|
||
|
|
dim_f_set=2048
|
||
|
|
elif modelhash == '7051d7315c04285e94a97edcac3f2f76':
|
||
|
|
modeltype = 'b'
|
||
|
|
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
|
||
|
|
stemset_n = '(Bass)'
|
||
|
|
compensate = 1.03597672895
|
||
|
|
source_val = 0
|
||
|
|
n_fft_scale_set=16384
|
||
|
|
dim_f_set=2048
|
||
|
|
else:
|
||
|
|
try:
|
||
|
|
f = open(f"lib_v5/filelists/model_cache/mdx_model_cache/{modelhash}.json")
|
||
|
|
mdx_model_de = json.load(f)
|
||
|
|
modeltype = mdx_model_de["modeltype"]
|
||
|
|
noise_pro = mdx_model_de["noise_pro"]
|
||
|
|
stemset_n = mdx_model_de["stemset_n"]
|
||
|
|
compensate = mdx_model_de["compensate"]
|
||
|
|
source_val = mdx_model_de["source_val"]
|
||
|
|
n_fft_scale_set = mdx_model_de["n_fft_scale_set"]
|
||
|
|
dim_f_set = mdx_model_de["dim_f_set"]
|
||
|
|
except:
|
||
|
|
modeltype = 'Not Set'
|
||
|
|
noise_pro = 'Not Set'
|
||
|
|
stemset_n = 'Not Set'
|
||
|
|
compensate = 'Not Set'
|
||
|
|
source_val = 'Not Set'
|
||
|
|
n_fft_scale_set='Not Set'
|
||
|
|
dim_f_set='Not Set'
|
||
|
|
|
||
|
|
|
||
|
|
model_params = modeltype, noise_pro, stemset_n, compensate, source_val, n_fft_scale_set, dim_f_set
|
||
|
|
|
||
|
|
return model_params
|