Embedding projector #301
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Embedding projector #301
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This was referenced Sep 17, 2025
* add test for scale intensity range percentiles transform * randomize test data * add decollate * detect leading slashes * configurable label column * fix typo * configurable example shape * type hint * fix example array * format * auto-align validation fov names * Adding some batched transforms for MAE training (#284) * Add batched transforms for MAE training - BatchedRandFlipd - BatchedRandSharpend - BatchedRandLocalPixelShufflingd - BatchedRandHistogramShiftd - BatchedRandZStackShiftd - BatchedRand3DElasticd * Revert existing files to original state Keep only new transform files and necessary imports * Fix import sorting in new transform files * Fix import formatting in __init__.py * Format code with ruff formatter * bugfix for device * ruff format fix * wip: random crop * format * use gather operation for cropping * register batched random crop * use unfold and bench * add dict version for random spatial crop * lint * benchmark crop * rename flip file * use tensorstore to stack * rename in register * add notebook to showcase transforms * batched center crop * batched gaussian noise * test and add to notebook * fix docstring * test random flip * add map version of batched gaussian noise * fix noise scaling and shifting * per-sample random flip * fix gaussian blur * rename blur to smooth to match monai * update smoothing tests * sigma-based truncation * print timer results * random adjust contrast * wrap monai * random scale intensity * update tests * allow final crop override * add center crop to example * remove redundant call method * check gamma value * use batched center crop * fix import * wip: fix gathering * limit worker to 1 * wip: execute augmentations in data hook * use the full loop for profiling * wip: update concat wrapper * fix negative sampling * update tests * revert to use threads * cache tensorstore arrays * update default num_workers * skip transforms for example array * relax flaky randomness test * explicitly configure cache pool * use new iohub API * only check cache when opening * fix transform initialization * remove unecessary tipletdatamodule inits * explain num_workers in the docstring * updating paths for profiling * fixed batch randintensityscale in the notebook --------- Co-authored-by: Ritvik <[email protected]> Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
* Adding annotation typings This PR takes a first stab at standardizing the labels and annotation columns for our datasets with the hope to merge annotations across datasets easily. * ruff format * changing the labels to dicts * format * distinction between cell cycle and cell division labels * ruff format --------- Co-authored-by: Ziwen Liu <[email protected]>
* add example for visualizing the shearing transform * plot dimensions in a loop * fix comment * ruff --------- Co-authored-by: Ziwen Liu <[email protected]>
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This PR addresses #155 and supercedes #217, adding the embedding projector example for logging with TensorBoard