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Workshop - High-precision classification of sound
This project forked from goodai/mlprague2019
Workshop - High-precision classification of sound
######################################################################## # ML Prague 2019 # Workshop # High-precision classification of sound ######################################################################## ##### Requirements for the workshop # Linux instructions (Windows instructions are the same unless said so in the comments) # Download and install anaconda for python 3.7 # download from https://www.anaconda.com/distribution/#download-section # Run anaconda prompt, then create conda env with python 3.6 (because conda does not support tensorflow on 3.7): conda create -n sound python=3.6.8 # Unset PYTHONPATH to avoid installation problems export PYTHONPATH= # On Windows, use: set PYTHONPATH= # Change to the directory where you will work with the workshop code cd sound_workshop # Activate env source activate sound # On Windows, use: activate sound # Install jupyter notebook if not present already conda install jupyter # Install conda core conda install numpy pandas scikit-learn tqdm scipy -y # Install pytorch conda install pytorch torchvision cudatoolkit=10.0 -c pytorch # Install requirements pip install pywavelets pycwt resampy eyed3 pydub soundfile # additionally 'pip install python-magic-bin' on Windows # Install tensorflow conda install tensorflow # Get VGGish data wget https://storage.googleapis.com/audioset/vggish_model.ckpt # on Windows, just download using browser wget https://storage.googleapis.com/audioset/vggish_pca_params.npz # on Windows, just download using browser # Get some sample wavs # download from https://drive.google.com/file/d/1izMGO_2DquUu0RGdI4GfJm41UJDUJbBP/view # we'll move these files to the appropriate folders during the workshop # download a pre-trained ResNet model # run python from command line, then: from torch.utils.model_zoo import load_url load_url("https://download.pytorch.org/models/resnet18-5c106cde.pth") # at the beginning of the workshop, you'll be provided with additional code (units of MB) that will be used during the workshop # In anaconda prompt: source activate sound # On Windows, use: activate sound # Clone the git repository (or copy from the provided flash drive). git clone https://github.com/GoodAI/mlprague2019.git cd mlprague2019 # Move the downloaded vggish*.ckpt and vggish*.npz to code/lib/vggish/ # Unzip all the wav files from wavs.zip into mlprague2019/wavs/ export PYTHONPATH=. # On Windows, use: set PYTHONPATH=. jupyter notebook # Click on MLPrague Demo.ipynb # In the third cell, change 'cuda' to 'cpu' if your machine doesn't have cuda capability
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