0.11.0

🚀 Features

Move tracking data preprocessing into `deepcell.data.tracking` @willgraf (#554)

What

• Update the adjacency matrix data from to a sparse tensor to significantly reduce memory footprint.
• Move Track and concat_tracks functions from deepcell-tracking to deepcell.data.tracking. They are really just .trk preprocessing and are unnecessary outside of prepare_data.
• Update temporal_slice to not slice into padded frames.
• Bump deepcell-tracking to 0.5.0.

Why

• Continue to upgrade the tracking model to make it more usable.
• The temporal_slice fix should improve the precision metrics of the model by not training on padded data.

🐛 Bug Fixes

Update numpy version constraints in pyproject.toml @willgraf (#563)

What

• Update numpy version constraints to match setup.py.

Why

• Fixes #559.

Revert `deepcell.data.tracking.prepare_dataset` to process concatenated Tracks. @willgraf (#561)

What

• Revert the change to prepare_dataset that allows it to process .trks files.

Why

• This change caused complications downstream (primarily in using different train and val files) and is not useful.

Update the training a tracking model notebook. @willgraf (#558)

What

• Fix the filter_and_flatten function.
• Add the graph_layer argument to the model call.

Why

• This function was not filtering the padded data properly, fixing it resolves the training issues.
• Improve overall clarity of options for tracking models.

🧰 Maintenance

Bump the version to 0.11.0. @willgraf (#564)

What

• Update the package version to 0.11.0.

Why

• Getting ready for the next release.

Minor updates to README @willgraf (#562)

What

• Pin docutils to 0.16 to resolve readthedocs build failures
• Add a monthly downloads badge
• Clean up grammar and whitespace.

Why

• General improvement for the README

Update models to latest trained tracking model. @willgraf (#560)

What

• Retrain tracking models using SparseTensors

Why

• Provide the latest and greatest models in the next release.