Parts of the code are untested on Windows (in particular, training a new model). If you don't have much experience with Anaconda, python or the shell, here are more detailed instructions. Note that Demucs is not supported on 32bits systems (as Pytorch is not available there).
- First install Anaconda with Python 3.7 or more recent, which you can find here.
- Start the Anaconda prompt.
Then, all commands that follow must be run from this prompt.
If you have graphic cards produced by nVidia with more than 6GiB of memory, you can separate tracks with GPU acceleration. To achieve this, you must install Pytorch with CUDA. If Pytorch was already installed (you already installed Demucs for instance), first run python.exe -m pip uninstall torch torchaudio
.
Then visit Pytorch Home Page and follow the guide on it to install with CUDA support.
Start the Anaconda prompt, and run the following bash
conda install -c conda-forge ffmpeg
python.exe -m pip install -U demucs PySoundFile
To upgrade Demucs, simply run python.exe -m pip install -U demucs
, from the Anaconda prompt.
Then to use Demucs, just start the Anaconda prompt and run:
demucs -d cpu "PATH_TO_AUDIO_FILE_1" ["PATH_TO_AUDIO_FILE_2" ...]
The "
around the filename are required if the path contains spaces.
The separated files will be under C:\Users\YOUR_USERNAME\demucs\separated\demucs\
.
You can use the following command to separate an entire folder of mp3s for instance (replace the extension .mp3
if needs be for other file types)
cd FOLDER
for %i in (*.mp3) do (demucs -d cpu "%i")
If you have an error saying that mkl_intel_thread.dll
cannot be found, you can try to first run
conda install -c defaults intel-openmp -f
. Then try again to run the demucs
command. If it still doesn't work, you can try to run first set CONDA_DLL_SEARCH_MODIFICATION_ENABLE=1
, then again the demucs
command and hopefully it will work 🙏.
If you get a permission error, please try starting the Anaconda Prompt as administrator.