update instance segmentation visualisation#57
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merge #56 first |
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Optuna GridSampler-based grid search over CPD non-rigid registration parameters (w, beta, lmd, maxiter), evaluated by mean Landmark Registration Error (LRE) between corresponding landmarks. - matchmaker/cpd_parameter_tuning/: optimization, landmark embedding, dataset-specific beta-range suggestion, defaults and README - workflows/cpd_optimization.smk: input_to_n5 -> add_landmarks -> prealignment_with_lm -> rigid_alignment_with_lm -> optimize_cpd - examples/cpd_optimization_config.yaml: example config (nest axis_orientation under prealignment to match the workflow/registration config convention) - matchmaker/utils/vis.py: add plot_landmark_qc and a title param for visualize_displacement_field (used by the tuning trial plots) - environment.yml: enable optuna Stacked on the visualisation branch (#57), which provides the PINK/CYAN colormaps that add_landmarks imports. Target branch: dev. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Visualization changes:
LABELcolormap and logic inplot_three_slicesto display label images with distinct colors usinglabel2rgb, improving interpretability of segmentation outputs. (matchmaker/utils/vis.py,matchmaker/prealignment.py,matchmaker/raw_to_n5.py)plots/subdirectory, improving output file organization. (matchmaker/cpd_nonrigid_registration.py)Other:
condaenvironment specifications from all Snakemake workflow rulesmatchmaker/raw_to_n5.py,matchmaker/cpd_nonrigid_registration.py)