Changelog

All notable changes to BraggTrack will be documented in this file.

The format follows Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

Rolling-median threshold smoother (smooth_thresholds) for stable multi-frame segmentation
Outlier frame detection (flag_outlier_frames) via MAD-based statistics
Label projection by intensity (label_projection_by_intensity) — replaces broken labels.max(axis=k)
MIP-floor masking via 2-D Otsu (otsu_floor_from_mip)
Tri-axis segmented mask visualisation in demo notebook
Semantic MIP gallery and PCA embedding space plots
Google Colab support with auto-install cell and "Open in Colab" badge
CI matrix (Python 3.10/3.11/3.12) with pip caching and notebook execution job
Optional dependency groups: [torch], [notebook], [dev]
BRAGGTRACK_DATA_ROOT env var for custom data locations
Ruff linting and formatting configuration
PEP 561 py.typed marker

Seed floor now uses robust peak reference (p99.99) instead of absolute max
Default seed_response_percentile raised from 99.5 to 99.95
torch and transformers moved to optional [torch] extra (bare install is lightweight)

Critical threshold domain mismatch: intensity Otsu was applied to LoG response domain
Spot count instability across scans (11/22/36 → 18/20/16 on bundled data)
Label projection picking highest label ID instead of brightest voxel's label

Initial release: discovery, segmentation (Otsu + connected components), tracking (Hungarian + lifecycle DAG)
Week 1: beamline adapter, scan discovery, validation
Week 2: classical LoG segmentation, h-maxima seeds, seeded watershed
Week 3: position+shape cost, per-axis gating, NetworkX lifecycle graph
Week 4: multi-view MIPs, mock/DINOv2 encoder, geometry+semantic cost, alpha/beta ablation
CLI tools: inspect, validate, segment-synthetic, segment-dataset, track-dataset, embed-dataset
Bundled ESRF-ID03 sample data (3 scans, 100×250×250 uint16)