Deepcell

🧰 Maintenance

<details>
<summary>Update Tensorflow to 2.8 msschwartz21 (595)</summary>

This PR updates tensorflow to 2.8 and drops support for python 3.6. The following changes were necessary to make this upgrade possible:
- Change imports from `tensorflow.python.keras` to `tensorflow.keras` which was a change introduced with tensorflow 2.6
- Remove convolutional recurrent layers and their functionality from featurenet and panopticnet. Key functions that were used in the convolutional recurrent layer are no longer available in keras.
- Change imports from `tensorflow.keras` to `keras`: `keras_parameterized`, `conv_utils`, `test_utils`
- Drop support for python 3.6

I retrained the nuclear model in the model-registry using this branch of deepcell and the performance was comparable.

To dos before reviewing:

- [x] Fix requirements that reference github branches
- [x] Update setup.py with new requirements
- [x] Remove git installation from Dockerfile
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🧰 Maintenance

<details>
<summary>Release numpy upper bound msschwartz21 (125)</summary>

This PR supports https://github.com/vanvalenlab/deepcell-tf/pull/595 which upgrades tensorflow to 2.8 and allows new versions of numpy.
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🐛 Bug Fixes

<details>
<summary>Correct dice property to return dice statistic msschwartz21 (122)</summary>

Addresses the bug identified in 121.
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🧰 Maintenance

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<summary>Update copyright to 2022 msschwartz21 (123)</summary>

Also bump up version for the next release
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🚀 Features

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<summary>Remove `correct_drift` to support the new `skimage` release 0.19.0. willgraf (119)</summary>

- Use `segmentation.watershed` instead of `morphology.watershed`.
- Remove `correct_drift` (Fixes 6) and `register_translation` is removed in 0.19.x.
- Set array slices with tuples to prevent warnings.
- Update `skimage` version requirements to avoid bug in `peak_local_max` in 0.16.x and 0.17.x.
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🐛 Bug Fixes

<details>
<summary>Pin python-version to 3.8 for PyPI deployment. willgraf (120)</summary>

numpy restriction for the toolbox requires Python < 3.10
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<details>
<summary>Remove `correct_drift` to support the new `skimage` release 0.19.0. willgraf (119)</summary>

- Use `segmentation.watershed` instead of `morphology.watershed`.
- Remove `correct_drift` (Fixes 6) and `register_translation` is removed in 0.19.x.
- Set array slices with tuples to prevent warnings.
- Update `skimage` version requirements to avoid bug in `peak_local_max` in 0.16.x and 0.17.x.
</details>

<details>
<summary>Set Recall, Precision, and SEG to all have same scale. willgraf (118)</summary>

Precision and SEG were being multiplied by 100 while Recall was not. This removes the 100x casting to make all metrics be in the same range [0, 1].

Additionally, fixes the `norecursedirs` value in `pytest.ini` to be space-delimited instead of comma-delimited.

Finally, pins `coveralls<3.3.0` to prevent a breaking change in the latest release.

Fixes 117
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🧰 Maintenance

<details>
<summary>Move `compute_overlap_3D` into `compute_overlap.pyx` willgraf (116)</summary>

No need to have each function in their own files.
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🚀 Features

<details>
<summary>Move tracking data preprocessing into `deepcell.data.tracking` willgraf (554)</summary>

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.

</details>

🐛 Bug Fixes

<details>
<summary>Pin `scikit-image` to < 0.19.0. willgraf (119)</summary>

Resolves a breaking change in the new release causing import issues.
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