haoheliu / 2021-ismir-mss-challenge-cws-presunet

Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.

2021-ismir-mss-challenge-cws-presunet's Issues

分离任务遇到ImportError错误

环境：CentOS 8.2，Anaconda3-2021.05（
Conda虚拟环境：Python3.8

安装命令：pip3 install -r requirements.txt

执行命令：python3 main.py -i example/test/xuemaojiao.wav -o example/results

遇到错误为：

Traceback (most recent call last):
  File "main.py", line 1, in <module>
    from predictor import SubbandResUNetPredictor
  File "/root/2021-ISMIR-MSS-Challenge-CWS-PResUNet/predictor.py", line 11, in <module>
    from demucs_predictor import DemucsPredictor
  File "/root/2021-ISMIR-MSS-Challenge-CWS-PResUNet/demucs_predictor.py", line 33, in <module>
    from demucs.utils import apply_model, load_model  # noqa
ImportError: cannot import name 'apply_model' from 'demucs.utils' (/root/anaconda3/lib/python3.8/site-packages/demucs/utils.py)

Thanks very much!!!!

I have not tried it yet, but I have been looking for software for 3 months to separate the noise of keystrokes from my music, I recorded it on a dictaphone in nature, and this noise of impacts terribly cuts my ears, if really your software will be able to help me (I will try later when there is a stable internet for downloading repo), I will be grateful to you for a thousand years!

Equally Divided Subband and Complex Spectrogram

Hi, I've read your paper and have a few questions,

1. As lower frequency contains more information, will the result be better if the subband is not equally divided? Perhaps log-scale? (and maybe add another transformation so that they have the same shape to concatenate.)
   I'd like to try it, yet I'm not sure how the filters (models/filters/*.mat) are generated.
2. If I understand it correctly, the U-Net cannot see the phase information,

   2021-ISMIR-MSS-Challenge-CWS-PResUNet/models/resunet_conv1_vocals/model.py

   Line 195 in 2f84db8

   sp, cos_in, sin_in = self.f_helper.wav_to_mag_phase_subband_spectrogram(input)

   
   since only sp is forwarded to U-Net.
   I've tried adding phase on other channels, so that the input to the U-Net will be (batch, channel*2, time, frequency), and the rest of the code is the same. But the result is worse. Do you have any thoughts on this?

Thanks a million!

PROBLEMS USING CWS-PResUNet ON WINDOWS

Hello, I am facing difficulties trying to use CWS-PResUNet on Windows 10, see below the logs of the problem I am having, if you can let me know where the problem is, I await your feedback, I will be very grateful thank you.

(base) C:\Users\lucas\CWS>``

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Building wheels for collected packages: torch-stoi, aicrowd-api, demucs, diffq, julius, audioread, resampy, progressbar, typing, mir-eval, pesq, pystoi
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  Building wheel for typing (setup.py) ... done
  Created wheel for typing: filename=typing-3.7.4.3-py3-none-any.whl size=26308 sha256=39ae383c669e6592a133ddf74f66c27cd510de6b6ac702f1d230776ab4c519b7
  Stored in directory: c:\users\lucas\appdata\local\pip\cache\wheels\5e\5d\01\3083e091b57809dad979ea543def62d9d878950e3e74f0c930
  Building wheel for mir-eval (setup.py) ... done
  Created wheel for mir-eval: filename=mir_eval-0.6-py3-none-any.whl size=96514 sha256=1376f8f0e69d284d5e046c2284a80c38efbf6d9d661c982931ddf12b3ab1b82f
  Stored in directory: c:\users\lucas\appdata\local\pip\cache\wheels\1c\47\0b\416b95d5fceba56809699852c33ae5291ffd2f0e73181ffd6c
  Building wheel for pesq (setup.py) ... error
  ERROR: Command errored out with exit status 1:
   command: 'C:\ProgramData\Anaconda3\python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\lucas\\AppData\\Local\\Temp\\pip-install-n_qyux9y\\pesq_ed38c459ee364f729530065fe03e90dc\\setup.py'"'"'; __file__='"'"'C:\\Users\\lucas\\AppData\\Local\\Temp\\pip-install-n_qyux9y\\pesq_ed38c459ee364f729530065fe03e90dc\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d 'C:\Users\lucas\AppData\Local\Temp\pip-wheel-k9wuzi4j'
       cwd: C:\Users\lucas\AppData\Local\Temp\pip-install-n_qyux9y\pesq_ed38c459ee364f729530065fe03e90dc\
  Complete output (22 lines):
  running bdist_wheel
  running build
  running build_py
  creating build
  creating build\lib.win-amd64-3.8
  creating build\lib.win-amd64-3.8\pesq
  copying pesq\__init__.py -> build\lib.win-amd64-3.8\pesq
  copying pesq\cypesq.pyx -> build\lib.win-amd64-3.8\pesq
  copying pesq\dsp.h -> build\lib.win-amd64-3.8\pesq
  copying pesq\pesq.h -> build\lib.win-amd64-3.8\pesq
  copying pesq\pesqio.h -> build\lib.win-amd64-3.8\pesq
  copying pesq\pesqmain.h -> build\lib.win-amd64-3.8\pesq
  copying pesq\pesqpar.h -> build\lib.win-amd64-3.8\pesq
  copying pesq\dsp.c -> build\lib.win-amd64-3.8\pesq
  copying pesq\pesqdsp.c -> build\lib.win-amd64-3.8\pesq
  copying pesq\pesqmod.c -> build\lib.win-amd64-3.8\pesq
  running build_ext
  cythoning pesq/cypesq.pyx to pesq\cypesq.c
  C:\ProgramData\Anaconda3\lib\site-packages\Cython\Compiler\Main.py:369: FutureWarning: Cython directive 'language_level' not set, using 2 for now (Py2). This will change in a later release! File: C:\Users\lucas\AppData\Local\Temp\pip-install-n_qyux9y\pesq_ed38c459ee364f729530065fe03e90dc\pesq\cypesq.pyx
    tree = Parsing.p_module(s, pxd, full_module_name)
  building 'cypesq' extension
  error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
  ----------------------------------------
  ERROR: Failed building wheel for pesq
  Running setup.py clean for pesq
  Building wheel for pystoi (setup.py) ... done
  Created wheel for pystoi: filename=pystoi-0.3.3-py2.py3-none-any.whl size=7781 sha256=ab6a0da4d3b71a56a2d6fa38302a42952458aa93800d6047716b2e3cb3833adf
  Stored in directory: c:\users\lucas\appdata\local\pip\cache\wheels\62\35\75\c07f0861a60fb8aacf44fdd5c8c214a224a6c9edb4a4e1402f
Successfully built torch-stoi aicrowd-api demucs diffq julius audioread resampy progressbar typing mir-eval pystoi
Failed to build pesq
Installing collected packages: pyasn1, rsa, pyasn1-modules, oauthlib, multidict, cachetools, yarl, requests-oauthlib, google-auth, async-timeout, torch, tensorboard-plugin-wit, tensorboard-data-server, protobuf, markdown, jmespath, grpcio, google-auth-oauthlib, fsspec, aiohttp, absl-py, torchmetrics, torchaudio, tensorboard, smmap, pytorch-ranger, pystoi, pyDeprecate, pesq, mir-eval, ffmpeg-python, einops, cached-property, botocore, win32-setctime, torch-stoi, torch-optimizer, stempeg, SoundFile, s3transfer, resampy, redis, pytorch-lightning, pyaml, pooch, pb-bss-eval, lameenc, julius, humanfriendly, huggingface-hub, gitdb, diffq, audioread, asteroid-filterbanks, typing, torchvision, torchlibrosa, tensorboardX, setuptools-scm, pynvml, progressbar, openunmix, norbert, musdb, loguru, librosa, GitPython, demucs, coloredlogs, boto3, asteroid, aicrowd-api
  Attempting uninstall: fsspec
    Found existing installation: fsspec 0.9.0
    Uninstalling fsspec-0.9.0:
      Successfully uninstalled fsspec-0.9.0
    Running setup.py install for pesq ... error
    ERROR: Command errored out with exit status 1:
     command: 'C:\ProgramData\Anaconda3\python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\lucas\\AppData\\Local\\Temp\\pip-install-n_qyux9y\\pesq_ed38c459ee364f729530065fe03e90dc\\setup.py'"'"'; __file__='"'"'C:\\Users\\lucas\\AppData\\Local\\Temp\\pip-install-n_qyux9y\\pesq_ed38c459ee364f729530065fe03e90dc\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:\Users\lucas\AppData\Local\Temp\pip-record-v7qod0sz\install-record.txt' --single-version-externally-managed --compile --install-headers 'C:\ProgramData\Anaconda3\Include\pesq'
         cwd: C:\Users\lucas\AppData\Local\Temp\pip-install-n_qyux9y\pesq_ed38c459ee364f729530065fe03e90dc\
    Complete output (20 lines):
    running install
    running build
    running build_py
    creating build
    creating build\lib.win-amd64-3.8
    creating build\lib.win-amd64-3.8\pesq
    copying pesq\__init__.py -> build\lib.win-amd64-3.8\pesq
    copying pesq\cypesq.pyx -> build\lib.win-amd64-3.8\pesq
    copying pesq\dsp.h -> build\lib.win-amd64-3.8\pesq
    copying pesq\pesq.h -> build\lib.win-amd64-3.8\pesq
    copying pesq\pesqio.h -> build\lib.win-amd64-3.8\pesq
    copying pesq\pesqmain.h -> build\lib.win-amd64-3.8\pesq
    copying pesq\pesqpar.h -> build\lib.win-amd64-3.8\pesq
    copying pesq\dsp.c -> build\lib.win-amd64-3.8\pesq
    copying pesq\pesqdsp.c -> build\lib.win-amd64-3.8\pesq
    copying pesq\pesqmod.c -> build\lib.win-amd64-3.8\pesq
    running build_ext
    skipping 'pesq\cypesq.c' Cython extension (up-to-date)
    building 'cypesq' extension
    error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
    ----------------------------------------
ERROR: Command errored out with exit status 1: 'C:\ProgramData\Anaconda3\python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\lucas\\AppData\\Local\\Temp\\pip-install-n_qyux9y\\pesq_ed38c459ee364f729530065fe03e90dc\\setup.py'"'"'; __file__='"'"'C:\\Users\\lucas\\AppData\\Local\\Temp\\pip-install-n_qyux9y\\pesq_ed38c459ee364f729530065fe03e90dc\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:\Users\lucas\AppData\Local\Temp\pip-record-v7qod0sz\install-record.txt' --single-version-externally-managed --compile --install-headers 'C:\ProgramData\Anaconda3\Include\pesq' Check the logs for full command output.


**(base) C:\Users\lucas\CWS>python main.py -i example/test/xuemaojiao.wav -o example/results -s vocals bass drums other**
Loading demucs model...
Downloading: "https://dl.fbaipublicfiles.com/demucs/v3.0/demucs-e07c671f.th" to ./utils/demucs_checkpoints\checkpoints\demucs-e07c671f.th
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 0.99G/0.99G [06:46<00:00, 2.61MB/s]
Downloading the weight of model for the vocal track
wget https://zenodo.org/record/5175846/files/epoch%3D49-val_loss%3D0.0902_trimed.ckpt?download=1 -O models/resunet_conv8_vocals/checkpoints/vocals/epoch=49-val_loss=0.0902_trimed.ckpt
--2021-08-27 19:50:10--  https://zenodo.org/record/5175846/files/epoch%3D49-val_loss%3D0.0902_trimed.ckpt?download=1
Resolving zenodo.org (zenodo.org)... 137.138.76.77
Connecting to zenodo.org (zenodo.org)|137.138.76.77|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 904040650 (862M) [application/octet-stream]
Saving to: 'models/resunet_conv8_vocals/checkpoints/vocals/epoch=49-val_loss=0.0902_trimed.ckpt'

=49-val_loss=0.0902_trimed.ckpt                        4%[====>                                                         49-val_loss=0.0902_trimed.ckpt                         4%[====>                                                         9-val_loss=0.0902_trimed.ckpt                          4%[====>                                                         -val_loss=0.0902_trimed.ckpt                           4%[====>                                                         val_loss=0.0902_trimed.ckpt                            5%[====>                                                         al_loss=0.0902_trimed.ckpt       2_trimed.ckpt                                          5%[=====>                                                                                                                ]  50,59M  2,51MB/s    eta 5m 3_trimed.ckpt                                           5%[=====>                                                        trimed.ckpt                                            5%[=====>                                                        rimed.ckpt                                             5%[======>                                                       imed.ckpt                                              6%[======>                                                       med.ckpt                                               6%[======>                                                       ed.ckpt                                                6%[======>                                                       d.ckpt                                                 6%[======>                                                       .ckpt                                                  6%[======>                                                       ckpt                                                   6%[======>                                                       kpt                                                    6%[======>                                                       pt                                                     6%[======>                                                       t                                                      6%[======>                                                                                                              6%[======>                                                                                                          m   6%[======>                                                                   models/resunet_conv8_vocals/checkpoints/vocals/epoch 100%[=====================================================================================================================>] 862,16M  2,57MB/s    in 5m 42s

2021-08-27 19:55:55 (2,52 MB/s) - 'models/resunet_conv8_vocals/checkpoints/vocals/epoch=49-val_loss=0.0902_trimed.ckpt' saved [904040650/904040650]

Downloading the weight of model for the other track
wget https://zenodo.org/record/5175846/files/epoch%3D33-val_loss%3D0.4293_trimed.ckpt?download=1 -O models/resunet_joint_training_other/checkpoints_nov/other/epoch=33-val_loss=0.4293_trimed.ckpt
--2021-08-27 19:55:55--  https://zenodo.org/record/5175846/files/epoch%3D33-val_loss%3D0.4293_trimed.ckpt?download=1
Resolving zenodo.org (zenodo.org)... 137.138.76.77
Connecting to zenodo.org (zenodo.org)|137.138.76.77|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 425901062 (406M) [application/octet-stream]
Saving to: 'models/resunet_joint_training_other/checkpoints_nov/other/epoch=33-val_loss=0.4293_trimed.ckpt'

models/resunet_joint_training_other/checkpoints_nov/ 100%[=====================================================================================================================>] 406,17M  2,72MB/s    in 2m 42s

2021-08-27 19:58:38 (2,51 MB/s) - 'models/resunet_joint_training_other/checkpoints_nov/other/epoch=33-val_loss=0.4293_trimed.ckpt' saved [425901062/425901062]

Loading vocal model...
Traceback (most recent call last):
  File "main.py", line 22, in <module>
    submission.prediction_setup()
  File "C:\Users\lucas\CWS\predictor.py", line 72, in prediction_setup
    self.v_model = self.reload(v_model_path, Conv8Res(channels=2, target="vocals"), nsrc=2)
  File "C:\Users\lucas\CWS\predictor.py", line 81, in reload
    model = model.load_from_checkpoint(pth) if (len(pth) != 0) else model
  File "C:\ProgramData\Anaconda3\lib\site-packages\pytorch_lightning\core\saving.py", line 153, in load_from_checkpoint
    model = cls._load_model_state(checkpoint, strict=strict, **kwargs)
  File "C:\ProgramData\Anaconda3\lib\site-packages\pytorch_lightning\core\saving.py", line 201, in _load_model_state
    keys = model.load_state_dict(checkpoint["state_dict"], strict=strict)
  File "C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1406, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for UNetResComplex_100Mb:
        Missing key(s) in state_dict: "wav_spec_loss.f_helper.istft.ola_window", "f_helper.istft.ola_window".
        Unexpected key(s) in state_dict: "wav_spec_loss.f_helper.istft.reverse.weight", "wav_spec_loss.f_helper.istft.overlap_add.weight", "f_helper.istft.reverse.weight", "f_helper.istft.overlap_add.weight".