The following is a short introduction to this research project. Please see the longer report.
This is a research project I conducted under the mentorship of professor Julian McAuley in my winter quarter of freshman year at UC San Diego. I applied a stacked GAN architecture to 3D voxels from the ShapeNet datase to produce high-fidelity fake models. I spent a total of around 10 weeks on the project and would like to continue to work on it in the future. Some results can be seen in the report in the subsection Experiments > Analysis of Generations.
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- A default Sphinx project; see sphinx-doc.org for details
│
├── models <- Trained and serialized models, model predictions, or model summaries
│ ├── cfg <- CFG files for models
│ ├── csv <- CSV logs of epoch and batch runs
│ ├── json <- JSON representation of the models
│ ├── predictions <- Predictions generated the train models and their best weights
│ ├── weights <- Best weights for the models
│ └── yaml <- YAML representation of the models
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data <- Scripts to download or generate data
│ │ └── make_dataset.py
│ │
│ ├── features <- Scripts to turn raw data into features for modeling
│ │ └── build_features.py
│ │
│ ├── logging <- Scripts to improve python logging
│ │ └── log_utils.py
│ │
│ ├── models <- Scripts to train and test models and then use trained models to make
│ │ │ predictions
│ │ ├── create_model.py
│ │ ├── predict_model.py
│ │ └── train_model.py
│ │
│ └── visualization <- Scripts to create exploratory and results oriented visualizations
│ ├── stats.py
│ └── visualize.py
│
└── tox.ini <- tox file with settings for running tox; see tox.testrun.org
Project based on the cookiecutter data science project template. #cookiecutterdatascience