O/j5dZddlmZddlZd dZd dZd dZ ddZd dZ dd Z d d Z dd Z y)aO ![sigsep logo](https://sigsep.github.io/hero.png) Open-Unmix is a deep neural network reference implementation for music source separation, applicable for researchers, audio engineers and artists. Open-Unmix provides ready-to-use models that allow users to separate pop music into four stems: vocals, drums, bass and the remaining other instruments. The models were pre-trained on the MUSDB18 dataset. See details at apply pre-trained model. This is the python package API documentation. Please checkout [the open-unmix website](https://sigsep.github.io/open-unmix) for more information. )utilsNc@ddd}ddlm}|ddg}tjdd d }i}|D]m}|d dd |}|rGtj j |||} |j| d|j|j||||<o|S)Nzraten_fft bandwidthinb_bins nb_channels hidden_sizemax_bin map_locationFstrict modelr rbandwidth_to_max_bintorchhubload_state_dict_from_urlload_state_dictevalto) targetsdevice pretrained target_urlsr r target_modelstarget target_unmix state_dicts U/root/repos/pocs/video-evals/.venv/lib/python3.12/site-packages/openunmix/__init__.py umxse_specr- sPNK !W%((gTUSGM - ASV`gh  ;;KrCrDrEr r rFrGr3rrFrrrHs r,umx_specrOrJr.c nddlm}t|||}||||dddd|| j|} | S) a] Open Unmix 2-channel/stereo BiLSTM Model trained on MUSDB18 Args: targets (str): select the targets for the source to be separated. a list including: ['vocals', 'drums', 'bass', 'other']. If you don't pick them all, you probably want to activate the `residual=True` option. Defaults to all available targets per model. pretrained (bool): If True, returns a model pre-trained on MUSDB18-HQ residual (bool): if True, a "garbage" target is created niter (int): the number of post-processingiterations, defaults to 0 device (str): selects device to be used for inference wiener_win_len (int or None): The size of the excerpts (number of frames) on which to apply filtering independently. This means assuming time varying stereo models and localization of sources. None means not batching but using the whole signal. It comes at the price of a much larger memory usage. filterbank (str): filterbank implementation method. Supported are `['torch', 'asteroid']`. `torch` is about 30% faster compared to `asteroid` on large FFT sizes such as 4096. However, asteroids stft can be exported to onnx, which makes is practical for deployment. rr0r2rEr rGrDr4)rr1rOr#rLs r,umxrQsQH!WV SM#%  bj r.cDddlm}ddddd}|gd}tjd d d }i}|D]m}|d dd|}|rGtj j |||} |j| d|j|j||||<o|S)Nrrz:https://zenodo.org/records/5069601/files/bass-2ca1ce51.pthz;https://zenodo.org/records/5069601/files/drums-69e0ebd4.pthz;https://zenodo.org/records/5069601/files/other-c8c5b3e6.pthzrCrDrEr r rFrGr rrFrrrHs r, umxl_specrS s MNNP K6((gTUSGM - ASWahi  ;;Kr\s<1hD   3lD   3lD   5r.