import json def get_vr_download_list(list): with open("lib_v5/filelists/download_lists/vr_download_list.txt", "r") as f: text=f.read().splitlines() list = text return list def get_mdx_download_list(list): with open("lib_v5/filelists/download_lists/mdx_download_list.txt", "r") as f: text=f.read().splitlines() list = text return list def get_demucs_download_list(list): with open("lib_v5/filelists/download_lists/demucs_download_list.txt", "r") as f: text=f.read().splitlines() list = text return list def get_mdx_demucs_en_list(list): with open("lib_v5/filelists/ensemble_list/mdx_demuc_en_list.txt", "r") as f: text=f.read().splitlines() list = text return list def get_vr_en_list(list): with open("lib_v5/filelists/ensemble_list/vr_en_list.txt", "r") as f: text=f.read().splitlines() list = text return list def get_download_links(links, downloads=''): f = open(f"lib_v5/filelists/download_lists/download_links.json") download_links = json.load(f) if downloads == 'Demucs v3: mdx': url_1 = download_links['Demucs_v3_mdx_url_1'] url_2 = download_links['Demucs_v3_mdx_url_2'] url_3 = download_links['Demucs_v3_mdx_url_3'] url_4 = download_links['Demucs_v3_mdx_url_4'] url_5 = download_links['Demucs_v3_mdx_url_5'] links = url_1, url_2, url_3, url_4, url_5 if downloads == 'Demucs v3: mdx_q': url_1 = download_links['Demucs_v3_mdx_q_url_1'] url_2 = download_links['Demucs_v3_mdx_q_url_2'] url_3 = download_links['Demucs_v3_mdx_q_url_3'] url_4 = download_links['Demucs_v3_mdx_q_url_4'] url_5 = download_links['Demucs_v3_mdx_q_url_5'] links = url_1, url_2, url_3, url_4, url_5 if downloads == 'Demucs v3: mdx_extra': url_1 = download_links['Demucs_v3_mdx_extra_url_1'] url_2 = download_links['Demucs_v3_mdx_extra_url_2'] url_3 = download_links['Demucs_v3_mdx_extra_url_3'] url_4 = download_links['Demucs_v3_mdx_extra_url_4'] url_5 = download_links['Demucs_v3_mdx_extra_url_5'] links = url_1, url_2, url_3, url_4, url_5 if downloads == 'Demucs v3: mdx_extra_q': url_1 = download_links['Demucs_v3_mdx_extra_q_url_1'] url_2 = download_links['Demucs_v3_mdx_extra_q_url_2'] url_3 = download_links['Demucs_v3_mdx_extra_q_url_3'] url_4 = download_links['Demucs_v3_mdx_extra_q_url_4'] url_5 = download_links['Demucs_v3_mdx_extra_q_url_5'] links = url_1, url_2, url_3, url_4, url_5 if downloads == 'Demucs v3: UVR Models': url_1 = download_links['Demucs_v3_UVR_url_1'] url_2 = download_links['Demucs_v3_UVR_url_2'] url_3 = download_links['Demucs_v3_UVR_url_3'] url_4 = download_links['Demucs_v3_UVR_url_4'] url_5 = download_links['Demucs_v3_UVR_url_5'] links = url_1, url_2, url_3, url_4, url_5 if downloads == 'Demucs v2: demucs': url_1 = download_links['Demucs_v2_demucs_url_1'] links = url_1 if downloads == 'Demucs v2: demucs_extra': url_1 = download_links['Demucs_v2_demucs_extra_url_1'] links = url_1 if downloads == 'Demucs v2: demucs48_hq': url_1 = download_links['Demucs_v2_demucs48_hq_url_1'] links = url_1 if downloads == 'Demucs v2: tasnet': url_1 = download_links['Demucs_v2_tasnet_url_1'] links = url_1 if downloads == 'Demucs v2: tasnet_extra': url_1 = download_links['Demucs_v2_tasnet_extra_url_1'] links = url_1 if downloads == 'Demucs v2: demucs_unittest': url_1 = download_links['Demucs_v2_demucs_unittest_url_1'] links = url_1 if downloads == 'Demucs v1: demucs': url_1 = download_links['Demucs_v1_demucs_url_1'] links = url_1 if downloads == 'Demucs v1: demucs_extra': url_1 = download_links['Demucs_v1_demucs_extra_url_1'] links = url_1 if downloads == 'Demucs v1: light': url_1 = download_links['Demucs_v1_light_url_1'] links = url_1 if downloads == 'Demucs v1: light_extra': url_1 = download_links['Demucs_v1_light_extra_url_1'] links = url_1 if downloads == 'Demucs v1: tasnet': url_1 = download_links['Demucs_v1_tasnet_url_1'] links = url_1 if downloads == 'Demucs v1: tasnet_extra': url_1 = download_links['Demucs_v1_tasnet_extra_url_1'] links = url_1 if downloads == 'model_repo': url_1 = download_links['model_repo_url_1'] links = url_1 if downloads == 'single_model_repo': url_1 = download_links['single_model_repo_url_1'] links = url_1 if downloads == 'exclusive': url_1 = download_links['exclusive_url_1'] url_2 = download_links['exclusive_url_2'] links = url_1, url_2, url_3 if downloads == 'refresh': url_1 = download_links['refresh_url_1'] url_2 = download_links['refresh_url_2'] url_3 = download_links['refresh_url_3'] links = url_1, url_2, url_3 if downloads == 'app_patch': url_1 = download_links['app_patch'] links = url_1 return links def provide_model_param_hash(model_hash): #v5 Models if model_hash == '47939caf0cfe52a0e81442b85b971dfd': model_params_set=str('lib_v5/modelparams/4band_44100.json') param_name=str('4band_44100') elif model_hash == '4e4ecb9764c50a8c414fee6e10395bbe': model_params_set=str('lib_v5/modelparams/4band_v2.json') param_name=str('4band_v2') elif model_hash == 'e60a1e84803ce4efc0a6551206cc4b71': model_params_set=str('lib_v5/modelparams/4band_44100.json') param_name=str('4band_44100') elif model_hash == 'a82f14e75892e55e994376edbf0c8435': model_params_set=str('lib_v5/modelparams/4band_44100.json') param_name=str('4band_44100') elif model_hash == '6dd9eaa6f0420af9f1d403aaafa4cc06': model_params_set=str('lib_v5/modelparams/4band_v2_sn.json') param_name=str('4band_v2_sn') elif model_hash == '5c7bbca45a187e81abbbd351606164e5': model_params_set=str('lib_v5/modelparams/3band_44100_msb2.json') param_name=str('3band_44100_msb2') elif model_hash == 'd6b2cb685a058a091e5e7098192d3233': model_params_set=str('lib_v5/modelparams/3band_44100_msb2.json') param_name=str('3band_44100_msb2') elif model_hash == 'c1b9f38170a7c90e96f027992eb7c62b': model_params_set=str('lib_v5/modelparams/4band_44100.json') param_name=str('4band_44100') elif model_hash == 'c3448ec923fa0edf3d03a19e633faa53': model_params_set=str('lib_v5/modelparams/4band_44100.json') param_name=str('4band_44100') elif model_hash == '68aa2c8093d0080704b200d140f59e54': model_params_set=str('lib_v5/modelparams/3band_44100.json') param_name=str('3band_44100.json') elif model_hash == 'fdc83be5b798e4bd29fe00fe6600e147': model_params_set=str('lib_v5/modelparams/3band_44100_mid.json') param_name=str('3band_44100_mid.json') elif model_hash == '2ce34bc92fd57f55db16b7a4def3d745': model_params_set=str('lib_v5/modelparams/3band_44100_mid.json') param_name=str('3band_44100_mid.json') elif model_hash == '52fdca89576f06cf4340b74a4730ee5f': model_params_set=str('lib_v5/modelparams/4band_44100.json') param_name=str('4band_44100.json') elif model_hash == '41191165b05d38fc77f072fa9e8e8a30': model_params_set=str('lib_v5/modelparams/4band_44100.json') param_name=str('4band_44100.json') elif model_hash == '89e83b511ad474592689e562d5b1f80e': model_params_set=str('lib_v5/modelparams/2band_32000.json') param_name=str('2band_32000.json') elif model_hash == '0b954da81d453b716b114d6d7c95177f': model_params_set=str('lib_v5/modelparams/2band_32000.json') param_name=str('2band_32000.json') #v4 Models elif model_hash == '6a00461c51c2920fd68937d4609ed6c8': model_params_set=str('lib_v5/modelparams/1band_sr16000_hl512.json') param_name=str('1band_sr16000_hl512') elif model_hash == '0ab504864d20f1bd378fe9c81ef37140': model_params_set=str('lib_v5/modelparams/1band_sr32000_hl512.json') param_name=str('1band_sr32000_hl512') elif model_hash == '7dd21065bf91c10f7fccb57d7d83b07f': model_params_set=str('lib_v5/modelparams/1band_sr32000_hl512.json') param_name=str('1band_sr32000_hl512') elif model_hash == '80ab74d65e515caa3622728d2de07d23': model_params_set=str('lib_v5/modelparams/1band_sr32000_hl512.json') param_name=str('1band_sr32000_hl512') elif model_hash == 'edc115e7fc523245062200c00caa847f': model_params_set=str('lib_v5/modelparams/1band_sr33075_hl384.json') param_name=str('1band_sr33075_hl384') elif model_hash == '28063e9f6ab5b341c5f6d3c67f2045b7': model_params_set=str('lib_v5/modelparams/1band_sr33075_hl384.json') param_name=str('1band_sr33075_hl384') elif model_hash == 'b58090534c52cbc3e9b5104bad666ef2': model_params_set=str('lib_v5/modelparams/1band_sr44100_hl512.json') param_name=str('1band_sr44100_hl512') elif model_hash == '0cdab9947f1b0928705f518f3c78ea8f': model_params_set=str('lib_v5/modelparams/1band_sr44100_hl512.json') param_name=str('1band_sr44100_hl512') elif model_hash == 'ae702fed0238afb5346db8356fe25f13': model_params_set=str('lib_v5/modelparams/1band_sr44100_hl1024.json') param_name=str('1band_sr44100_hl1024') else: try: with open(f"lib_v5/filelists/model_cache/vr_param_cache/{model_hash}.txt", "r") as f: name = f.read() model_params_set=str(f'lib_v5/modelparams/{name}') param_name=str(name) ('using text of hash worked') except: model_params_set=str('Not Found Using Hash') param_name=str('Not Found Using Hash') model_params = model_params_set, param_name return model_params def provide_model_param_name(ModelName): #1 Band if '1band_sr16000_hl512' in ModelName: model_params_set=str('lib_v5/modelparams/1band_sr16000_hl512.json') param_name=str('1band_sr16000_hl512') elif '1band_sr32000_hl512' in ModelName: model_params_set=str('lib_v5/modelparams/1band_sr32000_hl512.json') param_name=str('1band_sr32000_hl512') elif '1band_sr33075_hl384' in ModelName: model_params_set=str('lib_v5/modelparams/1band_sr33075_hl384.json') param_name=str('1band_sr33075_hl384') elif '1band_sr44100_hl256' in ModelName: model_params_set=str('lib_v5/modelparams/1band_sr44100_hl256.json') param_name=str('1band_sr44100_hl256') elif '1band_sr44100_hl512' in ModelName: model_params_set=str('lib_v5/modelparams/1band_sr44100_hl512.json') param_name=str('1band_sr44100_hl512') elif '1band_sr44100_hl1024' in ModelName: model_params_set=str('lib_v5/modelparams/1band_sr44100_hl1024.json') param_name=str('1band_sr44100_hl1024') #2 Band elif '2band_44100_lofi' in ModelName: 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