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Update dev/main #276

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Commits on Jul 22, 2024

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  9. fix: 🐛 fix how file stats are updated (#265)

    Prepend existing stats for file stats store to prevent overwriting.
    mzouink authored Jul 22, 2024
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Commits on Jul 23, 2024

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  2. fix: 🐛 Fix validation model loading.

    "validate_run" must now be called to do validation from run name. The Run must be preloaded and passed to call "validate" directly.
    rhoadesScholar committed Jul 23, 2024
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Commits on Jul 25, 2024

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Commits on Jul 29, 2024

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  3. black format

    mzouink committed Jul 29, 2024
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Commits on Jul 30, 2024

  1. fix plot hack

    mzouink committed Jul 30, 2024
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  2. fix import

    mzouink committed Jul 30, 2024
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Commits on Jul 31, 2024

  1. matplotlib plot

    mzouink committed Jul 31, 2024
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  3. Format Python code with psf/black push (#281)

    There appear to be some python formatting errors in
    f604f40. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
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    mzouink authored Jul 31, 2024
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Commits on Aug 2, 2024

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Commits on Aug 5, 2024

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  2. black format

    mzouink committed Aug 5, 2024
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  3. mypy fix

    mzouink committed Aug 5, 2024
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  5. Format Python code with psf/black push (#282)

    There appear to be some python formatting errors in
    cb300f5. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
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    mzouink authored Aug 5, 2024
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  6. fix circular import

    mzouink committed Aug 5, 2024
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  7. fix circular import

    mzouink committed Aug 5, 2024
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  8. fix validate

    mzouink committed Aug 5, 2024
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  9. fix tests

    mzouink committed Aug 5, 2024
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  11. Format Python code with psf/black push (#283)

    There appear to be some python formatting errors in
    81ec675. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Aug 5, 2024
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  12. Validate patch (#278)

    mzouink authored Aug 5, 2024
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  13. fix new pytorch error

    mzouink committed Aug 5, 2024
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  15. fix new pytorch error

    mzouink committed Aug 5, 2024
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Commits on Aug 7, 2024

  1. Format Python code with psf/black push (#285)

    There appear to be some python formatting errors in
    50d9833. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    rhoadesScholar authored Aug 7, 2024
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  2. Create CITATION.cff

    rhoadesScholar authored Aug 7, 2024
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  3. Update README.md

    rhoadesScholar authored Aug 7, 2024
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Commits on Aug 12, 2024

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  3. Fix small typos

    atc3 committed Aug 12, 2024
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Commits on Aug 13, 2024

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Commits on Aug 14, 2024

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  3. fix new pytorch error (#284)

    mzouink authored Aug 14, 2024
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  5. Fix small typos (#286)

    Fixed a couple small typos I encountered running examples
    mzouink authored Aug 14, 2024
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Commits on Sep 5, 2024

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  2. fix: 🐛 Fix datasplit._neuroglancer bug that happened with binarized…

    … arrays.
    
    Also set GT to automatically be a segmentation layer in neuroglancer, for run.visualize_pipeline
    rhoadesScholar committed Sep 5, 2024
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Commits on Sep 10, 2024

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  3. support max validation size

    mzouink committed Sep 10, 2024
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  4. fix import

    mzouink committed Sep 10, 2024
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  6. Format Python code with psf/black push (#290)

    There appear to be some python formatting errors in
    38a1b7e. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Sep 10, 2024
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  7. support nD

    mzouink committed Sep 10, 2024
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Commits on Sep 12, 2024

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  3. Feat: datasplit limit validation size (#289)

    Sometimes i want to speedup validation so as option we can limit
    validation size:
    `max_validation_volume_size = 600**3`
    mzouink authored Sep 12, 2024
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Commits on Sep 23, 2024

  1. local blockwise

    mzouink committed Sep 23, 2024
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Commits on Sep 24, 2024

  1. Format Python code with psf/black push (#295)

    There appear to be some python formatting errors in
    4583723. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    rhoadesScholar authored Sep 24, 2024
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Commits on Sep 25, 2024

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Commits on Sep 26, 2024

  1. all local changes

    mzouink committed Sep 26, 2024
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  2. all local changes

    mzouink committed Sep 26, 2024
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  3. local changes

    mzouink committed Sep 26, 2024
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Commits on Oct 2, 2024

  1. remove plot debug prints

    mzouink committed Oct 2, 2024
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  2. env DACAPO_OPTIONS_FILE

    mzouink committed Oct 2, 2024
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  3. remove trash

    mzouink committed Oct 2, 2024
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  5. Format Python code with psf/black push (#299)

    There appear to be some python formatting errors in
    d899c63. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Oct 2, 2024
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  6. Add bind parameters to neuroglancer instantiations (#297)

    This PR just adds a `bind_address` and `bind_port` parameter to all
    neuroglancer instantiation calls. The parameter defaults do not change
    prior behavior, and specifying bind parameters is useful for me to
    access neuroglancer via ssh tunnels to a cluster that does not normally
    expose any ports/addresses.
    mzouink authored Oct 2, 2024
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  8. Format Python code with psf/black push (#300)

    There appear to be some python formatting errors in
    7794118. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Oct 2, 2024
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  10. fix restart run

    mzouink committed Oct 2, 2024
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  11. batch norm params

    mzouink committed Oct 2, 2024
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  12. revert changes

    mzouink committed Oct 2, 2024
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  14. remove + uint8

    mzouink committed Oct 2, 2024
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  15. fix validate

    mzouink committed Oct 2, 2024
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  17. Format Python code with psf/black push (#301)

    There appear to be some python formatting errors in
    525f2fe. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Oct 2, 2024
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Commits on Oct 16, 2024

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  2. Add a minimal tutorial

    pattonw committed Oct 16, 2024
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  4. Basic tutorial (#303)

    Adds a simple tutorial start-to-finish tutorial for DaCapo.
    Still a few things left to resolve before its ready for merging:
    
    - [ ] Loss behaving strangely after the first validation (temporary
    solution involves giving an extra singleton dimension to the provided
    data)
    - [ ] Validation fails (we want to show validation loss/scores,
    validation outputs across iterations, and how to finally take the best
    iteration and apply it with the post processing to a volume manually)
    - [ ] stdout too verbose
    - [ ] plotting functions should be built into `DaCapo` (there are
    plotting functions, not sure how to include bokeh plots so I didn't dive
    too deep into this)
    mzouink authored Oct 16, 2024
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  6. fix tests

    mzouink committed Oct 16, 2024
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  7. fix validate tests

    mzouink committed Oct 16, 2024
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Commits on Oct 17, 2024

  1. Fix local predict (#305)

    mzouink authored Oct 17, 2024
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Commits on Oct 18, 2024

  1. working example

    mzouink committed Oct 18, 2024
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  2. fix dep

    mzouink committed Oct 18, 2024
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  4. Format Python code with psf/black push (#306)

    There appear to be some python formatting errors in
    25f3812. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Oct 18, 2024
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  5. tests works

    mzouink committed Oct 18, 2024
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  6. clean code

    mzouink committed Oct 18, 2024
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Commits on Oct 21, 2024

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  2. fix small bug

    pattonw committed Oct 21, 2024
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Commits on Oct 22, 2024

  1. Basic tutorial (#308)

    Add a basic in-memory postprocessor for watershed.
    
    It doesn't seem to be working that well because prediction seems broken.
    Here's a picture:
    
    ![Figure_1](https://github.com/user-attachments/assets/01c209e3-914e-44a2-85b4-70343b1a984f)
    
    I expect the postprocessor to work significantly better if the
    predictions are done with enough context to avoid the block artifacts
    and the predictions are post processed properly so that high affinity
    within objects leads to an affinity of 1 (it looks like its set to 0
    here), and a low affinity in the background leads to an affinity of 0
    (looks like it is set to 0.5 here)
    mzouink authored Oct 22, 2024
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  2. Basic tutorial (#304)

    @pattonw 
    Adds a simple tutorial start-to-finish tutorial for DaCapo.
    Still a few things left to resolve before its ready for merging:
    
    - [ ] Loss behaving strangely after the first validation (temporary
    solution involves giving an extra singleton dimension to the provided
    data)
    - [ ] Validation fails (we want to show validation loss/scores,
    validation outputs across iterations, and how to finally take the best
    iteration and apply it with the post processing to a volume manually)
    - [ ] stdout too verbose
    - [ ] plotting functions should be built into `DaCapo` (there are
    plotting functions, not sure how to include bokeh plots so I didn't dive
    too deep into this)
    mzouink authored Oct 22, 2024
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  5. improve watershed training and validation

    train on labels not mask, learn z affs for 3d objects, visualize with label colormap and without interpolation.
    pattonw committed Oct 22, 2024
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Commits on Oct 23, 2024

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  2. Basic tutorial (#310)

    add some improvements to DaCapo and the basic tutorial for learning
    instance segmentation through affs + watershed
    
    DaCapo:
    1) avoid doing any special postprocessing to convert to uint8 when
    writing out the predictions. just store as float32
    2) avoid converting back to float in the watershed postprocessor, just
    use the predictions as saved in the zarr.
    
    Tutorial:
    1) add labels colormap
    2) train z affs
    3) use valid padding
    
    Loss and validation plots are included below.
    There is still something strange happening with the loss after the first
    validation.
    The results still aren't as nice as they should be on such a simple toy
    dataset.
    
    
    ![Figure_2](https://github.com/user-attachments/assets/8badb5ca-5f4b-4e8e-821b-80f13c4987eb)
    
    ![Figure_3](https://github.com/user-attachments/assets/6f7276b6-5e3b-40b1-bcdc-ba0f2b865052)
    mzouink authored Oct 23, 2024
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  3. fix bug no kernel found

    mzouink committed Oct 23, 2024
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  4. fix bug no kernel found

    mzouink committed Oct 23, 2024
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  5. fix mypy error

    mzouink committed Oct 23, 2024
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  6. fix docs

    mzouink committed Oct 23, 2024
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  7. starter example

    mzouink committed Oct 23, 2024
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  8. better docs

    mzouink committed Oct 23, 2024
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  9. continue when generate error

    mzouink committed Oct 23, 2024
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  10. updating docs

    mzouink committed Oct 23, 2024
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  11. fix dep

    mzouink committed Oct 23, 2024
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  12. affinities example

    mzouink committed Oct 23, 2024
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  13. tqdm all in one line

    mzouink committed Oct 23, 2024
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  14. plot color fix

    mzouink committed Oct 23, 2024
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Commits on Oct 24, 2024

  1. tuto ipynb version

    mzouink committed Oct 24, 2024
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  2. install dep

    mzouink committed Oct 24, 2024
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  3. add google colab link

    David Ackerman committed Oct 24, 2024
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  4. feat: ✨ Add support for training on Apple M1/M2/M3 (mps) devices.

    Also add log printing of device used for training.
    rhoadesScholar committed Oct 24, 2024
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  7. Update gunpowder_trainer.py to swap to(device) and float() (#312)

    One more place where you have to(device) and then float().
    numpy default float is 64, so the to(device) will fail if the device is
    MPS that doesn't support float64.
    rhoadesScholar authored Oct 24, 2024
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Commits on Oct 28, 2024

  1. update dependencies

    pattonw committed Oct 28, 2024
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  2. update to funlib.persistence

    pattonw committed Oct 28, 2024
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Commits on Oct 30, 2024

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Commits on Nov 4, 2024

  1. Add optional probabilities to augmentations (#314)

    This PR adds an optional `augmentation_probability: float = 1.` argument
    to `ElasticAugment`, `IntensityAugment`, `SimpleAugment`.
    mzouink authored Nov 4, 2024
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Commits on Nov 5, 2024

  1. update predict local

    pattonw committed Nov 5, 2024
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  2. fix bug in constant array

    pattonw committed Nov 5, 2024
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  7. fix predict local

    pattonw committed Nov 5, 2024
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  9. update dependencies

    pattonw committed Nov 5, 2024
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  10. import zarr before using it

    pattonw committed Nov 5, 2024
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  11. fix local predict

    fixing batch dim bugs (batch norm requires batch dimension even in predict mode)
    Seems to also fix the strange loss spike. I think it was due to setting model into eval mode and then not resetting to training at the end
    pattonw committed Nov 5, 2024
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  12. update minimal tutorial

    pattonw committed Nov 5, 2024
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  13. Add support for most of the remaining arrays.

    Exceptions DVID and Resampled arrays
    pattonw committed Nov 5, 2024
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  14. black formatting

    pattonw committed Nov 5, 2024
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  15. fix mypy errors

    pattonw committed Nov 5, 2024
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Commits on Nov 6, 2024

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  5. Funlib persistence update (#322)

    Upgrade to funlib.persistence `0.5`.
    
    This update makes a one big improvement:
    Custom `Array` class no longer needed. We used this mostly just to apply
    preprocessing lazily to large arrays. New `funlib` `Array` class uses
    `dask` internally which comes with much better support for lazy array
    operations than we built for ourselves. The `ZarrArray` and `NumpyArray`
    class which were used extensively throughout `DaCapo` have now been
    replaced with simple `funlib.persistence.Array`s.
    
    A minor incompatibility:
    `funlib.persistence.Array` has a convention (for now) that all axes have
    names, but non-spatial axes have a "^" in their name. This will be fixed
    in the near future. For now, DaCapo convention needed to change a little
    bit to adapt to this. We now have to use "c^" and "b^" for channel and
    batch dimensions instead of just "c" and "b".
    
    TODOs:
    This pull request is not quire ready to merge. I pass the tests run with
    `pytest`, and the `minimal_tutorial` notebook executes. But there is a
    lot of code that is not tested. Specifically many of the `ArrayConfig`
    subclasses are not yet tested and some are missing implementations.
    
    Here are the Preprocessing array configs, whether or not their
    implementation is complete, and their code coverage:
    - [X] BinarizeArrayConfig 96%
    - [X] ConcatArrayConfig 60%
    - [X] ConstantArrayConfig 57%
    - [X] CropArrayConfig 69%
    - [X] DummyArrayConfig 91%
    - [ ] DVIDArrayConfig 90% (misleading, only skeleton implementation so
    not much to test)
    - [X] IntensitiesArrayConfig 75%
    - [X] LogicalOrArrayConfig 60%
    - [x] MergeInstancesArrayConfig 100% (misleading, no implementation so
    nothing to test)
    - [x] MissingAnnotationsMaskConfig 100% (misleading)
    - [x] OnesArrayConfig 100% (misleading)
    - [ ] ResampledArrayConfig 100% (misleading)
    - [x] SumArrayConfig 100% (misleading)
    - [x] TiffArrayConfig 0%
    - [X] ZarrArrayConfig 70%
    
    Best practice would be to add tests before merging, but I want to put
    this here so others can test it
    mzouink authored Nov 6, 2024
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  7. Format Python code with psf/black push (#324)

    There appear to be some python formatting errors in
    aeb77a6. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Nov 6, 2024
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  8. fix mps

    mzouink committed Nov 6, 2024
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  9. fix minor bug

    mzouink committed Nov 6, 2024
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  10. version 0.3.2

    mzouink committed Nov 6, 2024
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Commits on Nov 7, 2024

  1. cosem_starter

    mzouink committed Nov 7, 2024
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  2. fix table

    mzouink committed Nov 7, 2024
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Commits on Nov 11, 2024

  1. Add a roadmap to the docs

    pattonw committed Nov 11, 2024
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  2. improve formatting

    pattonw committed Nov 11, 2024
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  4. unet examples

    zouinkhim committed Nov 11, 2024
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Commits on Nov 12, 2024

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  2. use simplified data config

    pattonw committed Nov 12, 2024
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  3. add even simpler case

    pattonw committed Nov 12, 2024
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  4. update roadmap

    pattonw committed Nov 12, 2024
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  5. heavy unet tests

    mzouink committed Nov 12, 2024
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  7. Format Python code with psf/black push (#328)

    There appear to be some python formatting errors in
    1813190. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    rhoadesScholar authored Nov 12, 2024
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  10. Update index.rst

    mzouink authored Nov 12, 2024
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  11. Road map (#330)

    Adds a roadmap to the documentation
    mzouink authored Nov 12, 2024
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  14. test context

    mzouink committed Nov 12, 2024
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Commits on Nov 13, 2024

  1. fix arch dims

    mzouink committed Nov 13, 2024
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  4. more architecture tests

    mzouink committed Nov 13, 2024
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  5. add stored architecture test

    mzouink committed Nov 13, 2024
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  8. Data conventions (#329)

    Adds:
    1) A data doc that defines our expectations for data formatting
    2) Simplified data configuration classes
    3) Deprication warnings for old configuration classes
    mzouink authored Nov 13, 2024
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  9. index docs

    mzouink committed Nov 13, 2024
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  10. Data conventions (#335)

    mzouink authored Nov 13, 2024
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  13. Format Python code with psf/black push (#336)

    There appear to be some python formatting errors in
    e69bba2. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Nov 13, 2024
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  15. fix bug in cnnectome_unet return types

    The Architecture superclass says that we should be returning coordinates for these properties
    This is important because we regularly use these values in arithmetic where we expect to execute +-*/ element wise
    pattonw committed Nov 13, 2024
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  17. CNNectomeUNet: make the final conv pass in the upsample pass a bit mo…

    …re robust
    
    If we upsample, we probably want to apply a convolution to finetune the outputs rather than simply upsampling which we could do outside of a network. If we assume a kernel of size (3, 3, 3), it fails for 2D networks that process using kernels of size (1, 3, 3). We now just use the last kernel in the kernel size up. This is a bit more robust.
    pattonw committed Nov 13, 2024
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  18. Gunpowder Trainer: if the raw data doesn't have a channel dim, add it…

    … during training
    
    Otherwise the BatchNorm breaks
    pattonw committed Nov 13, 2024
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  19. Datasplit test fixture: use the voxel_size attribute for voxel size.

    This should probably just be switched to use `funlib.perisistence.prepare_ds`
    pattonw committed Nov 13, 2024
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  21. fix dims error

    mzouink committed Nov 13, 2024
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  23. Tests v0 3 5 (#338)

    Fixed a couple bugs
    1) CNNectome UNet wasn't following the api defined by the Architecture
    `ABC`. It was supposed to be returning `Coordinate` class instances for
    voxel_size, input_shape etc.
    2) CNNectome UNet had logical errors in the definition of kernel_size_up
    and down.
    3) New tests was expecting multi channel data for the 2D UNet and single
    channel for the 3D unet despite always getting single channel data.
    4) fix voxel_size attr in test fixtures
    mzouink authored Nov 13, 2024
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  25. Format Python code with psf/black push (#339)

    There appear to be some python formatting errors in
    dba261f. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Nov 13, 2024
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  26. revert change, fixed in unet

    mzouink committed Nov 13, 2024
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  27. organize

    mzouink committed Nov 13, 2024
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  28. add validate test

    mzouink committed Nov 13, 2024
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  30. Format Python code with psf/black push (#340)

    There appear to be some python formatting errors in
    392ddb3. This pull request
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Commits on Nov 14, 2024

  1. add unet2d/3d validation test

    mzouink committed Nov 14, 2024
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  3. Format Python code with psf/black push (#341)

    There appear to be some python formatting errors in
    fde6af2. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
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  4. add validation tests

    mzouink committed Nov 14, 2024
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  5. error handling 2d unet

    mzouink committed Nov 14, 2024
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  6. more iterations:

    mzouink committed Nov 14, 2024
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  8. Format Python code with psf/black push (#344)

    There appear to be some python formatting errors in
    2763f12. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
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Commits on Nov 15, 2024

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  3. Format Python code with psf/black push (#345)

    There appear to be some python formatting errors in
    97abfa0. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
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Commits on Nov 19, 2024

  1. autouse fork/spawn fixture so we test both

    this is necessary for getting compatibility with windows and macos
    pattonw committed Nov 19, 2024
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  3. simplify tests

    pattonw committed Nov 19, 2024
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  4. fix hard coded dimensions

    pattonw committed Nov 19, 2024
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  5. bugfix: typo

    pattonw committed Nov 19, 2024
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  6. bugfix: hardcoded dimensions

    pattonw committed Nov 19, 2024
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  7. simplify validation tests

    pattonw committed Nov 19, 2024
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  8. bugfix: Distance predictor wasn't working properly when run on single…

    … class prediction tasks
    pattonw committed Nov 19, 2024
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  9. Deprication warning:

    If the kernel size of the task is set to 3, then this will cause errors if you are trying to use a model with input shape `(1, y, x)`.
    The head should just be mapping the penultimate layer embeddings into the appropriate dimensions for the task so it desn't need a size larger than 1.
    pattonw committed Nov 19, 2024
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  12. bugfix: kernel size

    pattonw committed Nov 19, 2024
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  13. add todo on test

    pattonw committed Nov 19, 2024
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  14. Tests v0 3 5 (#346)

    Simplified the parameterized train test, and added validation. Fixed
    bugs that were found
    mzouink authored Nov 19, 2024
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  15. Configuration menu
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  16. Format Python code with psf/black push (#347)

    There appear to be some python formatting errors in
    85a6dda. This pull request
    uses the [psf/black](https://github.com/psf/black) formatter to fix
    these issues.
    mzouink authored Nov 19, 2024
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  17. v0.3.5

    mzouink committed Nov 19, 2024
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  18. fix mypy

    mzouink committed Nov 19, 2024
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  19. heavy unet tests - v0.3.5 (#327)

    multiple unitteststs + fixes
    mzouink authored Nov 19, 2024
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  20. Bump mwatershed

    vaxenburg committed Nov 19, 2024
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  21. Bump mwatershed (#348)

    mzouink authored Nov 19, 2024
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Commits on Dec 3, 2024

  1. fix small bug in simple dataset config

    `get_paths` gets the paths per dataset by searching for "raw", but should return the path to the dataset containing raw
    pattonw committed Dec 3, 2024
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  2. fix small bug in simple dataset config (#351)

    `get_paths` gets the paths per dataset by searching for "raw", but
    should return the path to the dataset containing raw
    mzouink authored Dec 3, 2024
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