Cellpose v3.0.5

Cellpose3 release with CLI, API and GUI support! Check out docs for updates to code: https://cellpose.readthedocs.io/en/latest/restore.html

Cellpose v3.0.1

first Cellpose 3 release!

cellpose v2.3.2

Last release of Cellpose 2 before update to Cellpose 3.

• fix slow stitching problem by only checking ROIs for stitching in current plane (issue #845)
• fix reshaping issue in flows from @mrariden ('mrariden-dynamics_reshape_fix' )
• add python 3.11 support from @harryzcy (#807)
• disable multiproc on windows from @mrariden
• fixes bug in 3D interpolation for multi-ROI masks
• disable gui autosave from @mrariden (#784)
• fix min size from @SimonBon (#781)
• fix imagej_roi_converter from @francodgstn (#828)
• fix torch version command (#831)
• fix zaxis=0 bug from @nickeener (#688)
• add a pyqt version to env from @rhoadesScholar (#849)
• fix for multimodel adding to gui from @landoskape (#839)

cellpose v2.2.2

Changes added to main branch

• Added functionality to allow saving ROIs in ImageJ-native format.
• Minor bug fix related to saving images with many objects thanks to @alix-simon
• Performance improvement using improved indexing thanks to @sophiamaedler
• Update Read the Docs to include a FAQ section, and misc RTD updates
• Add multithreading to 'outlines' exporting to speed up saving/execution time

cellpose v2.2.1

• fixing deprecation of np.bool
• @mrariden improved docs, added auto compilation of CLI page
• @FrickTobias fixed a bug for memory info (#647 )
• fixed version checking for torch 2.0 release

cellpose v2.1.1

Implementing some minor fixes and updates

• cellpose passes tests for python 3.9 and 3.10 across operating systems -- we still recommend python 3.8, particularly if you have issues with the install
• added option to use Mac M1 chip (if installed with torch) with command line argument --gpu device mps
• added option to run cellpose on a single file from the command like with --image_path as an alternative to --dir (#543)
• added new suggestion mode to suggest best Cellpose 2 model
• suppressed writing PNGs or outlines when no masks were found (#584)
• added docs for all functions (#554)
• fixed case sensitive image file detection (#555)
• allow eval method of Cellpose and CellposeModel to take as input torch arrays (#557)
• added the function io.add_model(/full/path/to/model) to add the model file to the hidden folder to use with GUI and CLI; can also access the function by running python -m cellpose --add_model /full/path/to/model (#558)
• fixed issue with cursor not allowing resizing (#545 )
• added mac instructions (#523)
• forced tiff saving for masks > 2**16 (#524)
• added pyqt5 import statement for windows 8.1 compatibility

cellpose v2.0.5

Small updates to Cellpose 2.0:

• added new notebook for running Cellpose 2.0
• model zoo model that was last clicked is highlighted in GUI
• number of ROIs in image is shown in the GUI
• added stitch_threshold option to GUI
• reenabled 3D annotations with "single stroke" option
• added imagecodecs dependency
• merged #494 and #495

cellpose v2.0.4

Cellpose 2.0 is here! Now you can train models in the loop with the Cellpose graphical interface. Upgrade to the latest version with

pip install cellpose --upgrade

Check out the twitter thread and preprint for details.

Read how to use human-in-the-loop yourself in the gui docs, and check out the full human-in-the-loop video.

Also, read more about the model zoo and how to use user-trained models in the models docs.

Cellpose v1.0.2

fixes some bugs with the GUI and the colab and min_train_masks

last stable release of Cellpose 1.0.

pip install cellpose==1.0.2

cellpose v1.0

stable release

• fixes some bugs in 0.8 with plotting and flow visualization in GUI
• merges pull request for stitch_threshold bug (#390)
• allows images with empty masks, depending on new flag --min_train_masks that is set to 5 by default. if fewer than min_train_masks in an image it is not used
• resample set to default True as in older releases
• model reloading per image turned off in CLI and class so that model is faster
• optional _masks.tif loading in GUI
• warning for user if masks are to be saved in np.uint32