Suite2p

Integrates all processing steps from motion correction to spike deconvolution, as listed in the Key Features, eliminating the need for multiple disparate tools.

Includes a powerful GUI for visualizing results, manually refining ROIs, and training custom classifiers, demonstrated in the provided GIF and twitter thread.

Features a machine learning model that distinguishes cells from artifacts and can be retrained on user data, improving accuracy over time as mentioned in the GUI description.

Backed by a leading research lab with regular updates, detailed documentation on Read the Docs, and an active community forum for troubleshooting, as shown by the badges and support links.