VisCy
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mehta-lab
computer vision models for single-cell phenotyping
BERT-style layer-wise LR decay following ConvNext v2 during fine-tuning.
The goal of the analysis is to identify infected and uninfected cells in a FOV using either viral sensor fluorescence or label-free images with nuclear instance segmentation label to output...
I am documenting here some of the questions that arose during the use of Viscy and the experience of running this during the DL@MBL course: I list them as tasks...
`viscy --help` prints a useful and succinct help message. But, `viscy subcommand --help` prints a lot of lightning CLI info that is not relevant, e.g., `viscy preprocess --help` prints: ```...
One inconvenient step in the mantis analysis pipeline is having to go and remember to change the scale metadata on the virtually stained predictions. Is it possible to write the...
Shows how to subclass the trainer with a placeholder method so the CLI parser can be reused. Adapted from https://github.com/Lightning-AI/lightning/issues/12302#issuecomment-1110425635. What we actually want is probably https://github.com/Lightning-AI/lightning/pull/18105.
The training loop lacks automated tests. Although unit-testing DL code is not as straightforward as other software, there are some strategies to improve the coverage. See these blog posts for...
We use intensity scaling and noise augmentations to make the virtual staining model invariant. We should leverage augmentations while keeping the training process stable and efficient. [This](https://arxiv.org/pdf/2203.03304.pdf) paper suggests a...