Single Shot Multi-Box Detector implementation in PyTorch.
This is the implementation used by SSDIR, a single-shot multi-object representation learning model.
Requirements:
- Install
poetry
(https://python-poetry.org/docs/#installation) - Use
poetry
to handle requirements- Execute
poetry add <package_name>
to add new library - Execute
poetry install
to create virtualenv and install packages
- Execute
To train the model use the train.py
script. Activate the environment by running poetry shell
and run python train.py --help
to see all the available options.
See all the available datasets in datasets directory. To train on multiscale MNIST dataset generate the dataset using multiscalemnist tool.
A trained model weights file can be used for training SSDIR model.
Use make
to run commands
make help
- show helpmake test
- run testsargs="--lf" make test
- run pytest tests with different arguments
make shell
- run poetry shell