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| title: AutoTab 🎸 | |
| emoji: 🎸 | |
| colorFrom: pink | |
| colorTo: indigo | |
| sdk: streamlit | |
| app_file: app.py | |
| # AutoTab 🎸 | |
| Eine App zur Vorhersage von Gitarren-Tabs basierend auf Audioaufnahmen. | |
| # Steps to test the installation | |
| - pip install -e . | |
| The above line installs autotab onto your machine | |
| - make first_npz | |
| the above line makes the first npz with two annotation files already stored in the guitarset annotation folder and two audio files already stored in your guitarset audio mic folder | |
| The output of this command is the npz files saved in data/spec_repr/c folder | |
| - make run_first_model | |
| The above line runs the first train of the model, only on the one file provided to you. NOTE : The Test phase of the model will fail, because you have only one file | |
| # Next steps | |
| - Download the entire GuitarSet from | |
| https://zenodo.org/record/1422265#.YZ0JEdBBwnK | |
| Make sure to select the GuitarSet_audio_and_annotation.zip 7.5GB | |
| Unzip and place into the GuitarSet Folder inside data folder. A place holder has already been made for you | |
| - If you wish to make new npz files, at the bottom of TabDataReprGen file, provide two numbers between 0 and 359 as n(must be even) and n + 1 in place of the 0 and 1 currently provided. Then | |
| - make first_npz | |
| - If you wish to train on this new npz file, search from the beginning of the file name in the data/spec_repr/full_id.csv file, and copy all lines connected to that file into the data/spec_repr/id.csv file. You can then | |
| - make run_first_model | |
| - (In Progress/TO DO) Parallel_Tab generation for all wav files | |
| - (In Progress/TO DO) Train model on multiple files | |
| # Data analysis | |
| - Document here the project: autotab | |
| - Description: This Project focuses on creating a CNN-Model to predict guitar tabluature based on a .wave input file. | |
| So far the model only detects a single instrument. | |
| - Data Source: Data from Audio Research Lab, along the Center for Digital Music at Queen Mary University. | |
| GuitarSet, a dataset that provides high quality guitar recordings alongside rich annotations and metadata. https://guitarset.weebly.com/ | |
| - Type of analysis: Training a model based on the Data and trying to predict an accurate tabluatur. | |
| Please document the project the better you can. | |
| # Startup the project | |
| The initial setup. | |
| Create virtualenv and install the project: | |
| ```bash | |
| sudo apt-get install virtualenv python-pip python-dev | |
| deactivate; virtualenv ~/venv ; source ~/venv/bin/activate ;\ | |
| pip install pip -U; pip install -r requirements.txt | |
| ``` | |
| Unittest test: | |
| ```bash | |
| make clean install test | |
| ``` | |
| Check for autotab in gitlab.com/{group}. | |
| If your project is not set please add it: | |
| - Create a new project on `gitlab.com/{group}/autotab` | |
| - Then populate it: | |
| ```bash | |
| ## e.g. if group is "{group}" and project_name is "autotab" | |
| git remote add origin git@github.com:{group}/autotab.git | |
| git push -u origin master | |
| git push -u origin --tags | |
| ``` | |
| Functionnal test with a script: | |
| ```bash | |
| cd | |
| mkdir tmp | |
| cd tmp | |
| autotab-run | |
| ``` | |
| # Install | |
| Go to `https://github.com/{group}/autotab` to see the project, manage issues, | |
| setup you ssh public key, ... | |
| Create a python3 virtualenv and activate it: | |
| ```bash | |
| sudo apt-get install virtualenv python-pip python-dev | |
| deactivate; virtualenv -ppython3 ~/venv ; source ~/venv/bin/activate | |
| ``` | |
| Clone the project and install it: | |
| ```bash | |
| git clone git@github.com:{group}/autotab.git | |
| cd autotab | |
| pip install -r requirements.txt | |
| make clean install test # install and test | |
| ``` | |
| Functionnal test with a script: | |
| ```bash | |
| cd | |
| mkdir tmp | |
| cd tmp | |
| autotab-run | |
| ``` | |