Jim Martens 08976dad82 | ||
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README.md | ||
pyproject.toml | ||
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setup.py | ||
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README.md
Master Thesis
Allows reproduction of results in my master thesis.
The package supports testing and evaluating SSD and Bayesian SSD. The results can be visualised.
Installation
Please install python header files of your Python version. Those are needed to compile the pycocotools with Cython upon installation.
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 for instructions on
installing the non-Python dependencies for tensorflow
.
Type the following to create the configuration file and to see the options:
tm-masterthesis config list
Especially the paths have to be set to the correct values.
Usage example
tm-masterthesis --help
Lists all available commands. As most commands are nested, it is advisable to request the help at different nesting levels.
tm-masterthesis config {get,set,list}
Allows for the modification and retrieval of the configuration values.
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.
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.
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 master thesis and might therefore not be of interest generally.
Development setup
Clone the repository locally. Then execute the following commands inside the repository:
git submodule init
git submodule update
pip install -e .
pip install 'git+https://github.com/philferriere/cocoapi.git#egg=pycocotools&subdirectory=PythonAPI'
Release History
- 0.3.0
- added cython dependency and information about required python header files
- 0.2.0
- added python 3.8 classifier
- 0.1.0
- first release
Meta
Jim Martens – @2martens – github@2martens.de
Distributed under the Apache 2.0 license. See LICENSE
for more information.
The package contains the ssd_keras implementation of Pierluigi Ferrari.
Contributing
- Fork it (https://github.com/2martens/masterthesis/fork)
- Create your feature branch (
git checkout -b feature/fooBar
) - Commit your changes (
git commit -am 'Add some fooBar'
) - Push to the branch (
git push origin feature/fooBar
) - Create a new Pull Request