Visualization

run_hybrid_visualizer(config) opens a repository-backed study browser with six views: study overview, datasource originals, real/synthetic anomaly variants, hybrid samples and their placements, metric-based evaluation, and the complete normalized data structure. The Datasource tab lists all ingested originals with source-name/ID search and filters for anomalous/control and annotated/unannotated samples. Images use automatic RGB display for three-channel arrays; channel, slice, contrast and mask overlays remain selectable for grayscale and 3D data. In every image view, use the mouse wheel to zoom around the pointer and drag with the left mouse button to pan. Double-click a panel or use Reset zoom to fit images again. Zoom persists across contrast, channel, mask and slice changes; selecting another sample resets it. Use Shift+wheel, the slice slider, or Up/Down keys to navigate 3D slices. The Evaluation tab also previews linked fused placement ROIs for cutout metrics. Use Placement ROI preview to choose among multiple placements of the same synthetic anomaly; available ROI files are preferred initially. Placement metrics always show their evaluated placement, and selecting a preview leaves the metrics and evaluation scope unchanged. Artifacts are loaded lazily and cached only while they are inspected. The data structure view can preview dependent records before moving their files into a recoverable .trash folder and removing the corresponding database records.

The visualizer can also be started for an existing study folder:

python -m hybrid_sample_generator.visualization /path/to/study --channel auto