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@dylanbannon dylanbannon released this 17 Sep 00:02
· 70 commits to master since this release
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Learn about vigilant mode.

This version of the Deepcell Kiosk was used to obtain the benchmarking results in the preprint Dynamic allocation of computational resources for deep learning-enabled cellular image analysis with Kubernetes.

The Deepcell Kiosk currently supports segmentation of individual live-cell images and tracking of cells across image stacks out of the box,. Furthermore, the architecture is flexible enough that, by extending the kiosk-redis-consumer repository, users can adapt the Deepcell Kiosk to support arbitrary image processing workflows. As example of this extensibility is available in the aforementioned preprint, where we implemented an augmented microscopy workflow.

Valid inputs to the Deepcell Kiosk include individual images or zip files of multiple images.

The Deepcell Kiosk is fully functional on Google Kubernetes Engine and autoscales using Kubernetes' built-in HPA functionality. These features will be supported on Amazon Web Services in a future release.

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