# Masterthesis > Allows reproduction of results in my masterthesis. [![Downloads][pypi-downloads]][pypi-url] ![License][pypi-license] ![Python versions][pypi-python-versions] The package supports testing and evaluating SSD and Bayesian SSD. The results can be visualised. ## Installation ```sh pip install twomartens.masterthesis pip install git+https://github.com/philferriere/cocoapi.git#egg=pycocotools&subdirectory=PythonAPI ``` The second line is important as Git dependencies cannot be specified in the `setup.py` file. Please refer to [GPU support][tf-gpu-support] for instructions on installing the non-Python dependencies for `tensorflow`. Type the following to create the configuration file and to see the options: ```sh tm-masterthesis config list ``` Especially the paths have to be set to the correct values. ## Usage example ```sh tm-masterthesis --help ``` Lists all available commands. As most commands are nested, it is advisable to request the help at different nesting levels. ```sh tm-masterthesis config {get,set,list} ``` Allows for the modification and retrieval of the configuration values. ```sh tm-masterthesis test {ssd,bayesian_ssd} iteration train_iteration ``` Tests the selected network, using `iteration` as identifier for the test run and `train_iteration` as identifier for the training iteration. If the config parameter `ssd_test_pretrained` is `True` then the training iteration is not relevant. ```sh tm-masterthesis evaluate {ssd,bayesian_ssd} iteration ``` Runs the evaluation process using the test results identified by `iteration`, evaluation results are saved under `iteration` under the evaluation path. ```sh tm-masterthesis visualise_metrics {ssd,bayesian_ssd} iteration ``` Uses the evaluation results stored under `iteration` and visualises it. The score JSON and the figure images are stored under `iteration` in a `visualise` folder under the output path. There are more commands but the rest can be very tightly linked to requirements in the masterthesis and might therefore not be of interest generally. ## Development setup Clone the repository locally. Then execute the following commands inside the repository: ```sh git submodule init git submodule update pip install -e . pip install git+https://github.com/philferriere/cocoapi.git#egg=pycocotools&subdirectory=PythonAPI ``` ## Release History * 0.1.0 * first release ## Meta Jim Martens – [@2martens](https://twitter.com/2martens) – github@2martens.de Distributed under the Apache 2.0 license. See ``LICENSE`` for more information. [https://github.com/2martens/](https://github.com/2martens/) ## Contributing 1. Fork it () 2. Create your feature branch (`git checkout -b feature/fooBar`) 3. Commit your changes (`git commit -am 'Add some fooBar'`) 4. Push to the branch (`git push origin feature/fooBar`) 5. Create a new Pull Request [dependencies]:https://img.shields.io/librariesio/release/pypi/twomartens.masterthesis.svg [pypi-license]: https://img.shields.io/pypi/l/twomartens.masterthesis.svg [pypi-url]: https://pypi.org/project/twomartens.masterthesis/ [pypi-downloads]: https://img.shields.io/pypi/dm/twomartens.masterthesis.svg [pypi-python-versions]: https://img.shields.io/pypi/pyversions/twomartens.masterthesis.svg [tf-gpu-support]: https://www.tensorflow.org/install/gpu