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Minor bug-fixes

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@lmanan lmanan released this 15 Jun 15:00
· 213 commits to main since this release
v0.2.3-tag
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Learn about vigilant mode.

A minor update since release v0.2.2. This includes:

  • Add display_zslice parameter and save_checkpoint_frequency parameter to configs dictionary here
  1. Support for visualization for setups when virtual_batch_multiplier > 1 is still missing.
  2. Also hardcoded install version of tifffile in setup.py here because latest version currently (2021.6.14) generates a warning message with imsave command while generating crops with bbbc010-2012 dataset. Will relax this version specification in release v0.2.4

TODOs include:

  1. Plan to update pytorch version to 1.9.0 in release v0.2.4 (currently pytorch version used is 1.1.0)
  2. Plan to add tile and stitch capability in release v0.2.4 for handling in large 2d and 3d images during inference
  3. Plan to add a parameter max_crops_per_image in release v0.2.4 to set an optional upper bound on number of crops extracted from each image
  4. Plan to save all instance crops and center crops as RLE files in release v0.2.4
  5. Plan to add an optional mask parameter during training which ignores loss computation from certain regions of the image in release v0.2.4
  6. Plan to deal with bug while evaluating var_loss and to have crops of desired size by additional padding.
  7. Plan to include support for more classes.
  8. Normalization for 3d ==> (0,1, 2)
  9. Make normalization as default option for better extensibility
  10. Parallelize operations like cropping
  11. Eliminate the specification of grid size in notebooks -set to some default value
  12. Simplify notebooks further
  13. Make colab versions of the notebooks
  14. Test center=learn capability for learning the center freely
  15. Add the ILP formulation for stitching 2d instance predictions
  16. Add the code for converting predictions from 2d model on xy, yz and xz slices to generate a 3D instance segmentation
  17. Add more examples from medical image datasets
  18. Add threejs visualizations of the instance segmentations. Explain how to generate these meshes, smoothen them and import them with threejs script.
  19. Padding with reflection instead of constant mode
  20. Include cluster_with_seeds in case nuclei or cell detections are additionally available
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