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Edgar Riba edited this page Oct 18, 2020 · 7 revisions

2020-10-08

Agenda

  • Announcements
  • Roadmap
  • Final discussion

Minutes

Announcements

  • Release v0.4.1 by mid October.
  • Pytorch v1.7 release by mid November
  • descriptors matching API and descriptors benchmark.
  • 3d augmentations API and more.
  • Next meeting after 0.5 release to discuss 0.7 roadmap.

Roadmap discussion

Final discussion

  • Find some tool to find out which part of the tests have to be run when there’s a modification.
  • Morphology module: collaboration [v0.6]
  • Find more collaborations and start integration to other frameworks: lightning, catalyst, monai, ROS.

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2020-09-09

Agenda

  • Association
  • Website
  • Open Technical Meetings
  • Marketing
  • Improve tutorials/examples

Minutes

Association

  • Create a legal entity so that we can operate and receive donations from third parties.
  • Edgar will check on that in Barcelona: need at least 3 people on the board, can be from any country.
  • Edgar and Stefano need to check on Gary to discuss about the relation between kornia and opencv.

Website

  • remodel the kornia.org website
  • define the web requirements we want before contacting the web developers.
  • hire a web developer: budget 200/300E, we want at least to maintain the website, include blog, etc.

Open Technical Meetings

  • We are organizing open meeting to get and receive feedback from the community.
  • Reach more users to feedback, create forms to for feedback.
  • Contact with companies using to self-promoting and collaborate.
  • Better define roadmaps and look for collaborators, etc.

Marketing

  • Need to coordinate social media presence.
  • Get more users, get donations.
  • Frequency of social media (plan and set schedule).

Improve tutorials/examples

  • Check tutorials and see how we could improve them.
  • Create kornia cheat-sheet.
  • Contact guy that made tutorials in turkish to translate in English.
  • Morphology module/tutorials.

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2020-04-24

Agenda

  • Next release
  • Discuss data augmentation API
  • Infrastructure, Testing
  • Documentation
  • Roadmap functionalities

Minutes

Next release v0.2.2

  • v0.2.2 after decopupling in augmentation to still support pytorch 1.4
  • v0.3.0 to align with pytorch v1.5 and torchvision v0.6

Discuss data augmentation API

  • for v0.3.0 we'll keep stick to the functional structure we have. We want to let user to override gen_params, apply and possibly gen_transformation and easily create new ops.
  • For next iterations, Jian proposes to include kornia.Sequential to chain operations.
  • Implement kornia.eye_like(n, tensor)
  • Target compatibility with albumentations and rising for next release.
  • torchvision plans: https://github.com/pytorch/vision/issues/1375

Infrastructure, Testing

  • Automate GPU using AWS credits and CircleCI -> Edgar
  • Edgar is meeting google collaborator to get TPUs for testing.
  • Edgar has nvidia jetson to test half precision
    • Will share resources with lightning
  • We need to test JIT: start by augmentation module.
  • Update testing framework using pytest tools
    • Pytest-cov
    • Pytest-mypy
  • Define minimal testing api (check functions)
    • check_is_tensor(tensor)
    • check_is_shape(tensor, tuple) # (2,3,4,4)
    • check_eq_shape(tensor1, tensor2, …) check_is_dtype(tensor, (torch.float32, torch.float64)) check_is_device(tensor, (‘cpu’, ‘cuda’)) -> tbd

Documentation

  • Update to pytorch style -> Edgar (almost done)
  • Verify all docs look good. Any tools for that?
    • Doctest ? make it incremental.

Next Roadmap functionalities

  • Old (0.2.1): https://github.com/kornia/kornia/issues/434
  • Luis will refactor warper module
    • AffineGridWarper -> AffineWarper. HomographyWarper, PerspectiveWarper (3d)
  • Volumetric (rising guys)
  • Features matching: kornia.feature.matching (edgar/dmytro)
    • Nn, snn, sinkhorn
  • homography/fundamental -> edgar
  • TBD: morphology

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2020-03-16

Agenda

  • Discuss data augmentation module

Minutes

  1. Allow data augmentation with branching -> for text.
  2. Other frameworks for data augmentation:
  1. Priorities:
  • Slower in CPU compared torchvision
    • compute final transformation and apply
    • create benchmarks
      • empirical test, not to rely on a specific framework
  • compare to torchvision using their parameters
  • different types of transforms
    • spatial transform
    • channel, pixel not move at all
    • gaussian noise, independent pixels

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