0.4.0

🚀 Features

Update Tracking Approach and Address Outstanding Bugs @MekWarrior (#53)

What

• End-to-End updates for DeepCell's approach to the tracking problem in live-cell imaging. A new Track object is introduced to hold track information and allow for augmentation using the new dataset builder module in deepcell-tf. This PR introduces breaking changes related to the previous LSTM and Siamese Neural Network (SNN) model architecture. The updated CellTracker object is intended for use with the inference model and neighborhood encoders generated and trained by the new graph-based tracking architecture in deepcell-tf. Additionally, the utils related to benchmarking have been updated and improved.

Why

• These updates represent the natural evolution of the repo's approach to tracking. It addresses key needs to further enable adoption of TF2 and dramatically improves tracking speed. At the same time, it address several bugs that have been uncovered since deepcell-tracking was first introduced.

---

This PR should also fix several old issues:

• Fixes #13 (Removes compute_distance)
• Fixes #14 (Prefetches all cell features, no repeated loops)
• Fixes #35 (removes _get_input_pairs)

🧰 Maintenance

Fix PyPI version badge URL. @willgraf (#49)

Update version to 0.4.0 @willgraf (#58)

Create release-drafter workflow to draft releases automatically. @willgraf (#59)