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