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@marcschefer marcschefer released this 17 Dec 16:06
· 259 commits to master since this release
0.16
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Learn about vigilant mode.

New features:

  • Model fitting improvements
    • Iterative deblending for model fitting
    • Custom user-made models can be provided in the form of ONNX compute graphs
    • Automatic fit resolution downgrade for very large models
    • Python priors are now evaluated in the C++ code for increased performance
    • Overall major improvements to stability, performance and memory usage

Changes that may require configuration files update:

  • Multi-thresholding and grouping of split sources are now on by default
  • In the model fitting Python configuration, source properties are now actual properties instead of getter functions: o.get_radius() => o.radius
  • Iterative model fitting is on by default, if needed the new system can be turned off with use_iterative_fitting(False) (not all improvements from this release are available in the old system)
  • Segmentation using a ML model was renamed from --segmentation-onnx-model to --segmentation-ml-model (experimental feature)
  • The Onnx property that performs a measurement using an Onnx compute graph is renamed to MLMeasurement
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