Motion Correction and CNMF visualizations should just work. CNMFE will work without "rcb" and "residuals" image_data_options.
:exclamation: Harware requirements The large CNMF visualizations with contours etc. usually require either a dedicated GPU or integrated GPU with access to at least 1GB of VRAM.
https://www.youtube.com/watch?v=GWvaEeqA1hw
After you have mesmerize-core installed:
pip install mesmerize-vizIf you want to use %gui qt you will need pyqt6 or PySide6:
pip install PyQt6
# or
pip install PySide6Click on different rows to view the results of different runs of motion correction, CNMF or CNMFE.
https://github.com/kushalkolar/mesmerize-viz/assets/9403332/41175c80-7bdf-4210-96d4-4913ae46568e
Explore components using the heatmap selector, or the component index slider. Auto-zoom into components if desired using the checkbox, set the zoom scale using the slider.
https://github.com/kushalkolar/mesmerize-viz/assets/9403332/c6d8cb7d-f99c-4771-8562-b890c9a18ae2
View the evaluation metrics by setting the contour colors based on the metrics. Select to show "all", or only "accepted" or only "rejected" components based on the current evaluation criteria. You can also choose to make the accepted or rejected components semi-transparent instead of entirely opague or invisible using the alpha slider.
Colormaps used:
accepted/rejected: Set1, accepted - blue, rejected - red
snr, r_values, and cnn_preds: spring: low value: pink, high value: yellow
https://github.com/kushalkolar/mesmerize-viz/assets/9403332/b2780212-c941-4306-b7de-45bfa49ab9cd
Interactively change the metric thresholds for the sliders. See the caiman docs for info on the evaluation params: https://caiman.readthedocs.io/en/latest/Getting_Started.html#component-evaluation
After setting the metric thresholds, you can manually accept or reject components by clicking on them and pressing "a" (accept) or "r" (reject) keys on your keyboard.
When you are happy with component evaluation, click "Save eval to disk". This overwrites the existing hdf5 file with the state of the hdf5 file as shown in the visualization, i.e. estimates.idx_components and estimates.edx_components_bad gets set with respect to the visualization.
https://github.com/kushalkolar/mesmerize-viz/assets/9403332/0e7b0b41-9360-456c-9c91-6bd74fedb11d
Install voila:
pip install voilaUse as a voila app (as shown in the demo video).
cd mesmerize-viz
voila examples/app.ipynb --enable_nbextensions=TrueNote that the voila app is a prototype