Native object-detection toolkit with registry-first model composition and a PyTorch Lightning runtime.
SimpleDet is designed to make detector development predictable and production-friendly:
- Build detector definitions with
simpledet.suite(Encoder, Neck, Head, Decoder, Detector specs). - Compile runtime plans that adapt layer dimensions automatically from actual encoder outputs.
- Run training, inference, and evaluation through native project-oriented workflows.
- Keep experimentation reproducible with explicit CLI and config-based project execution.
| Area | What you get |
|---|---|
| Model authoring | Declarative detector specs + registry-backed component assembly |
| Execution | Native PyTorch Lightning training, inference, and evaluation path |
| Adaptation | Automatic channel/shape alignment during model compilation |
| Packaging | Project-level run orchestration and validation commands |
| Catalog support | retinanet, retina, fcos, atss, gfl, vfnet, fovea, foveabox, reppoints, yolof, centernet, faster_rcnn, mask_rcnn, grid_rcnn, cascade_rcnn |
python -m pip install simpledetpython -m pip install "simpledet[cpu]"python -m pip install "simpledet[geo,plots]"git clone https://github.com/sirbastiano/SimpleDet.git
cd SimpleDet
python -m pip install -e ".[cpu]"python -m simpledet --version
python -m simpledet --check-runtime- Platforms: Linux, macOS, Windows
- Python: 3.10, 3.11, 3.12
- Runtime support: CPU stack via
simpledet[cpu](wheel-compatible dependencies are required for supported OS/Python pairs)
simpledet.suite: author specs, compose detector graphs, and compile native plans.simpledet.native: run native PyTorch Lightning model loops.simpledet.detectors: compatibility helpers for lightweight flows.simpledet._model_resolution: runtime shape and channel adaptation internals.
make venv
make sync
make sync-cpu
make build
make docs-audit
make checksimpledet/: Python source root used by packagingsimpledet/simpledet/: installable packagesimpledet/simpledet/native/: native Lightning runtime and model execution componentssimpledet/simpledet/suite/: detector specs, builders, and planning helperssimpledet/simpledet/_model_resolution.py: model-adaptation helperssimpledet/simpledet/detectors/: compatibility path for lightweight training/eval flowsdocs/: static documentation sitescripts/: repository verification and docs audit helperstests/: unit and packaging checks
python3 -m build
python3 -m twine check dist/*
PYTHONPATH=simpledet python3 -m unittest discover -s tests -p 'test*.py'SimpleDet is released under the MIT License.