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CellCounter v1.0.12 for macOS

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@Alperen-Gur Alperen-Gur released this 05 Sep 11:36
· 9 commits to main since this release
v1.0.12
4b4b26d

CellCounter v1.0.12 for macOS

This hotfix improves image previews and makes the first Cellpose model download visible, with clear errors when a connection stalls.

Requires macOS 15 or later. The app is a universal Intel and Apple Silicon build, ad-hoc signed and not notarized. See the installation guide.

Faster, steadier previews

  • Supported single-frame 8-bit PNG, JPEG and BMP images prepare their selected source channel or RGB luminance natively before Python startup. Scientific stacks, high-bit-depth data and unsupported pixel layouts retain the shared source reader.
  • Analysis setup shows a bounded original preview while preparing the selected channel. Changes to confidence, calibration or mask results no longer restart source decoding.
  • The representative-image picker starts with a valid selection and has an explicit empty state. Saved model selections also retain a matching picker tag.
  • Import completion keeps the presenting screen stable while the setup sheet is open, and the preview has a stable height to avoid unnecessary layout churn.

Clear first-use model setup

  • Cellpose 3 and 4 show model-loading stages and weight-download byte progress. Closing a partial download no longer reports success.
  • Stalled network operations time out after 30 seconds of inactivity. A slow download that continues receiving data can take longer overall.
  • Download failures include an actionable retry hint, preserved by the native error handler.
  • Images without scale metadata show a calibration explanation. Missing metadata is normal for many screenshots and does not indicate a segmentation failure; calibrated measurements still need a known scale.

If an older session was interrupted during first-use setup, reopen the app and resume its paused job from Processing. Keep the app open while weights download; completed weights are reused.

Focused validation

The native preview/training suite passed 15 tests, including four new preview cases; four Python startup regression tests passed. A local run using the reported fluorescence image and its saved settings completed Cellpose cyto3 segmentation on Apple GPU in 18.6 seconds, after a separate 66.8-second first-use checkpoint download. Images were not uploaded. Successful execution does not establish segmentation accuracy.

One optimized native helper call decoded the same image, prepared its source plane and encoded the preview in 146 milliseconds. This is a helper timing, not a cold-cache average or an end-to-end UI benchmark. The reported AppKit layout/drag warnings were not independently reproduced in a live UI session; this patch removes the identified presentation and sizing churn.

Windows and web releases are unchanged.

Download

Download CellCounter-v1.0.12.zip and its .sha256 checksum from the v1.0.12 release. Unzip and replace CellCounting.app in Applications after quitting the older copy.

ZIP SHA-256: 2e4ca7e4b59714b8ec8f99dbe52920e42524441400f3f3f67995d3a971f06bdd.

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