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Followup for multi-annotation trainings #8097

@daniel-wer

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@daniel-wer

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#8071 allows starting a job to train a model on multiple annotations, selected by id or uri. Follow-up wishes came up:

  • When training a model from within wk, currently all bounding boxes of all annotations need to have the same size. This restricts which training data can be combined. Slight variations in size are usually no big deal and one even sometimes decides to "waste" some training data, because that's better than not using the data at all. Also, this becomes even more relevant with the next point. This will also require changes in the worker which should use the smallest bounding box of all to guide the training_sample_size computation (and related values). https://github.com/scalableminds/voxelytics/pull/3796 and Relax bounding box requirements for model training #8222
  • It should be possible to select a resolution for each annotation which is the resolution that will be trained on. Many a time this is not the finest resolution (which is chosen currently). Only mags that exist both in the image data layer and the ground truth layer should be selectable. This is a frontend only issue.

Context

  • Specific to long-running jobs (set jobsEnabled=true in application.conf)
  • Specific to webknossos.org (set isDemoInstance=true in application.conf)

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