- Clone this repository and open its directory.
- Initialize and update the submodules (
git submodule update --init --recursive). -
Install the requirements using
conda env create --file=conda_env_cpu.ymlor
conda env create --file=conda_env.yml
for GPU acceleration.
requirements.txtandrequirements_all.txtare also provided as references, but are not needed when using theconda_env.ymlfiles.
Alternatively, you can also create a blankcondaenvironment (Python 3.10 or similar) and dopip install uvand then copy and paste and uncomment the long commenteduv pip install ...command in theconda_env.ymlfile.
This is probably the fastest option if your internet connection is fast. - The source code can be explored in the
src/directory. - Create an out directory (
mkdir out). -
Make sure your
PYTHONPATHhas been set correctly by running a command like
export PYTHONPATH=$PYTHONPATH:BASE_DIR/wavelet_resynthesis/wavelet_resynthesis,
- The source code is currently not documented, but don't hesitate to open an issue if you have any questions or comments.
-
You can conduct experiments by modifying and running
scripts/experiments.py.
christhetree/wavelet_resynthesis
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