0.12.1

🚀 Features

Create TFRecords for tracking datasets @vanvalen (#602)

What

• Added functionality to create TFRecords for tracking datasets

Why

• As the training datasets grow in size, they are no longer able to fit in memory (as is the case with image generators). Adding functionality for TFRecords will let us train on larger datasets as they are loaded dynamically from disk during training rather than into memory all at once.

🐛 Bug Fixes

Fix tracking model bug that pinned n_filters, encoder_dim and embedding_dim to 64 @vanvalen (#606)

What

• Fixed a bug that required the tracking model to have n_filters, encoder_dim, and embedding_dim be pinned to 64

Why

• Model optimization is going to require us to change these parameters to improve performance and reduce model size. This pull request makes that substantially easier by fixing this bug.

🧰 Maintenance

Bump version to 0.12.1 @msschwartz21 (#605)

Expose option for fixed crops in the Track data object @vanvalen (#607)

What

• Modify the Track class so that it allows hooks into get_image_features for crop_mode and norm

Why

• Creating the appearance image feature by cropping and resizing removes information about cell size that the model can use to make more accurate tracking predictions. A previous update to deepcell-tracking (vanvalenlab/deepcell-tracking#98) introduced the crop_mode (either 'fixed' or 'resize') and norm flags to get_image_features. This pull request exposes these flags to the Track class.

Bump `deepcell-tracking` to 0.6.0 @msschwartz21 (#603)

What

• Bump deepcell-tracking to the new minor release
• Update imports to match the reorganization introduced in this release

Update the docstring for `format_output_mesmer` @curlup (#601)

What

Doc-string for format_output_mesmer is now correctly saying "ValueError: if model output list is not len(4)"

Why

Because format_output_mesmer code diverged from the doc in what is expected length of model output list