Nightingale is a Python & Tensorflow codebase for training, exporting, inferencing, & evaluating the state-of-the-art SCRDet++ object detection model with ResNet backbone on NITF imagery. Nightingale's inference module is compatible with the OMITTED suite of products. The current version of Nightingale is configured for system single channel imagery.
Nightingale is for Computer Vision data scientists, researchers, or developers with access to the Intelligence Community (IC) Common Operating Environment (COE). You'll need a linux style GPU-accelerated computing environemnt with Jupyter Notebooks, such as users with a Redmine RLE account and access to RLE's JupyterHub or DGX systems. It is also for those interestd in object-aligned object detection or a OMITTED-compatible detector.
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