TCN Intermediate images (predicted images during training)
├── README.md <- Organizational chart of this project.
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├── data
│ ├── bdd_feu <- Bounds of the parameters to be used.
│ ├── raw <- Data generated by MatLab code with uniform distribution.
│ ├── train <- Data of the training sample.
│ ├── test <- Data of the testing sample.
│ ├── predicted <- Data (images only) predicted by the trained model.
│ └── intermediate <- Data generated during training (after each 10 epochs).
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├── docs <- Some useful materials as figures, ...
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├── models <- Trained model (to use for prediction).
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├── notebooks <- Jupyter notebooks.
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├── references <- Data dictionaries, manuals, and all other explanatory materials.
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├── reports <- Generated analysis.
│ └── figures <- Generated graphics and figures to be used in reporting.
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├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module.
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│ ├── timer.py <- Scripts to take into account the calculation time.
│ ├── heat_dist.py <- Scripts to generate raw data using (transformed MatLab code, uniform distribution).
│ ├── get_data.py <- Scripts to download or generate data.
│ ├── process.py <- Scripts to process data for training models.
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│ ├── model.py <- Scripts to build the architecture of the TCNN model.
│ ├── train.py <- Scripts to train the TCNN model.
│ ├── predict.py <- Scripts to generate new data (images) using trained model and test sample.
│ └── visualize.py <- Scripts to create exploratory and results oriented visualizations.
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└── TODO... <- TODO --------