napari-worm-neuron-annotator

napari-worm-neuron-annotator is a napari plugin for navigating and annotating read-only neuron bounding-box ROIs on 3D or 4D Image volumes.

The plugin keeps each data source in a separate role:

• the Image layer supplies the spatial axes, world transform, and Z-navigation context;
• the ROI array supplies neuron identity and box geometry;
• runtime Vectors and Points layers show boxes and optional text without writing them into a dense mask;
• an explicitly selected Labels layer can add a compatible mask overlay and checked/unchecked alpha control.

The plugin does not modify Image, ROI, or optional Labels source data.

Roadmap: Plugin-managed Labels are planned for deprecation. The primary workflow now uses Image + ROI-derived Vectors/Points, while an explicitly selected Labels layer remains available for compatibility. See the deferred deprecation decision.

Features

• Image + ROI operation without a Labels layer.
• Read-only loading of (T,N,K) ROI NPY arrays.
• Dynamic 2D bounding rectangles and 3D 12-edge wireframes.
• Stable per-neuron box colors derived from zero-based ROI identity.
• Checkable neuron list with a separate active neuron.
• All/None controls and cumulative Q/W navigation.
• Fixed canvas shortcuts for Z-slice and time-frame navigation.
• Active-neuron highlighting and view centering.
• Session-only whole-viewer rotation and screen-axis flip controls.
• View-preserving Z-layer display synchronized across Image and ROI overlays.
• Zero-based ROI annotation with optional Excel import/export.
• Optional Labels overlay with independent checked/unchecked alpha and exact RGB preservation.
• Automatic restoration of the original Labels colormap and opacity when the widget closes or switches to another Labels layer.

Installation

Install into an existing napari environment:

pip install napari-worm-neuron-annotator

For a fresh environment, install napari with its default Qt 6 backend:

pip install "napari-worm-neuron-annotator[all]"

Excel support alone is available through:

pip install "napari-worm-neuron-annotator[excel]"

The base plugin does not install or select a Qt binding. The napari environment owns the Qt backend; the convenience all extra delegates that choice to napari.

This release targets Python 3.11–3.14 and napari 0.8.x. See the napari 0.8 migration notes for the dependency and compatibility decisions.

Image + ROI workflow

1. Open an Image layer with (z,y,x) or (t,z,y,x) axes.
2. Open Plugins > Worm Neuron Annotator.
3. Select the Image layer, then load the ROI NPY file.
4. Click a neuron row to check and activate that ID.
5. Use the checkbox column to add or remove IDs from the persistent set.
6. Use Q and W to check and activate the previous or next valid ID without clearing IDs already checked.
7. Use All or None to check every ID or clear all checked/active IDs.

With the napari canvas focused, use G/H for the previous/next Z slice in 2D, J/K for the previous/next time frame of a 4D Image, and Shift-J/Shift-K to move backward/forward by 10 time frames. Navigation stops at the data bounds rather than wrapping. In an individual Z layer, G/H stays within that layer's half-open Z range.

The active row is bold and remains the current row. Unchecking the active ID clears the active state; unchecking another ID does not change the active neuron.

The ROI array defines the neuron list. You do not need a Labels layer for selection, box rendering, annotation, centering, time navigation, or Z-layer display.

Worm orientation

The Worm Orientation panel rotates the complete viewer clockwise by 0°, 90°, 180°, or 270° and can flip the final screen horizontally or vertically. Image, ROI boxes, optional text, Labels, and Z-layer views stay aligned because the controls change only napari's viewer axes and camera orientation. Source arrays and layer transforms are not modified.

Reset restores the viewer orientation captured for the current session. Closing the widget also restores that orientation. If you use napari's native transpose or camera-orientation controls, the resulting view becomes the new session baseline and the plugin controls return to their default state.

Optional Labels overlay

Select a Labels layer only when you need the mask overlay. Its shape, axes, scale, translation, and units must match the selected Image layer. The ROI array remains the identity source, and the Image layer remains the spatial authority.

The Labels Layer panel controls checked and unchecked label alpha. The defaults are 0.50 and 0.00. Alpha changes preserve each label's RGB value, and the widget restores the original colormap and opacity when it closes or switches to another Labels layer. The napari layer-list eye icon can hide the whole mask.

Deferred deprecation of plugin-managed Labels

The current release keeps the optional Labels integration and the legacy LabelManager Python and command aliases for compatibility. The public widget name is NeuronAnnotatorWidget, and napari lists only that widget.

A future compatibility migration may remove plugin-managed Labels after users have had time to move their Image + ROI workflows. No removal version is set. Source Labels data remains read-only during the migration period.

Z-layer display

The compact Z Layers panel separates a 3D volume along Z so individual depth ranges can be rendered without the other ranges obscuring them:

1. Select a compatible Image layer.
2. Inspect the current-time curve showing how many pixels in each Z slice are strictly above the editable threshold (default 170). Click the curve to add or remove a cut, or enter explicit cuts such as 4,10.
3. Click Split.
4. Use Show to select All or one generated layer.

Cuts use half-open Python ranges. For a volume with 18 Z slices, 4,10 creates [0,4), [4,10), and [10,18). A boundary slice belongs to the following layer.

All displays every generated Image layer using additive blending and all currently valid checked/active ROI overlays. Layer k displays only that Image range and the overlays whose box center Z belongs to the range. A box that crosses a cut is shown whole in the one layer containing its center.

When you explicitly bind compatible Labels, Split creates read-only view or lazy-slice proxies. All shows the complete source Labels and hides the proxies. Layer k hides the source and shows its matching proxy slice. The plugin never allocates a dense Labels copy.

Checked and active neuron identities remain global. In an individual layer, Q/W navigates only neurons assigned to that layer; other neurons remain in the list, are shown in gray, and keep operable checkboxes. Activating a gray row does not move the view outside the selected Z layer.

Generated Image layers use slices of NumPy arrays, memory maps, or Dask arrays rather than full-size zero-filled copies. Direct Zarr arrays should be wrapped as Dask arrays before splitting. The Image source must have (z,y,x) or (t,z,y,x) axes, axis-aligned volume depiction, and no clipping planes. Optional Labels must match its shape and spatial metadata. Clear removes generated Image and Labels layers and restores the source visibility captured before splitting. Normal napari eye icons may still override visibility until the next Show selection.

Launch the validated 20260304_w3_immobile dataset

The repository includes a ready-to-use launcher for the git-ignored local dataset at data/20260304_w3_immobile_npy:

pixi run launch-actual

It memory-maps volumes.npy and neuron_point_tuple.npy, opens napari, docks the navigator, and loads all 120 ROI identities. The launcher leaves its LOAD_OPTIONAL_LABELS validation toggle disabled by default. Enable it to memory-map neuron_mask.npy and exercise the optional Labels integration.

ROI input format

The ROI loader accepts a numeric NumPy array with shape:

(T, N, K), K >= 6

The first six fields are:

x_center, y_center, z_scaled, width, height, depth_scaled

Additional fields are ignored. The neuron ID is the index on the N axis:

neuron_id = 0 ... N - 1
label_value = neuron_id + 1
background label_value = 0

NaN, infinite values, non-positive sizes, and time points outside the source array are treated as missing observations. Missing neurons remain in the checkable list so that their global identity is stable, but Q/W skips them at the current time point.

Coordinate and time mapping

The plugin requires the selected Image layer to have one of these axis orders:

(z, y, x)
(t, z, y, x)

z_divisor, defaulting to 5, converts source z and depth coordinates:

z_index = z_scaled / z_divisor
depth_in_slices = depth_scaled / z_divisor

For a viewer that displays a cropped or strided time range:

source_t = volume_start + viewer_t * volume_stride

Configure volume_start and volume_stride before loading the NPY.

The derived ROI overlay layers copy scale, translation, axis labels, and units from the Image layer. Do not apply the z scale a second time in the ROI coordinates. Optional Labels never supply ROI colors or spatial metadata.

2D and 3D box display

Two managed Vectors layers are created after loading an ROI file:

• Neuron boxes – selected: checked, currently valid boxes colored by their stable neuron_id palette;
• Neuron box – active: the active box with a thick yellow outline.

Initially only the first valid neuron is checked and active. All includes all IDs in the selected layer, while None empties both box layers and the optional text overlay. Checked identities that are missing at the current time remain checked but are temporarily omitted from the geometry.

Enable Show selected box labels to place one text label at the center of each currently rendered checked box. The text uses the annotation table's biological value when present and otherwise falls back to the zero-based neuron_id. The third annotation column is not used for box labels. The option is off by default. Use Text color to choose a session-only label color that contrasts with the current Image colormap.

In 2D mode, the plugin draws four rectangle edges only when the current z slice intersects the box's half-open z range.

In 3D mode, each box is represented by 12 vector edges. Overlapping boxes remain independent vector records with a neuron_id feature. They may overlap visually, but one box does not erase the identity of another.

Vectors and the transparent Points text layer are derived display data. They are removed when the ROI is unloaded or the widget closes and are not saved as a separate annotation format.

Annotation

The digital column stores the zero-based ROI neuron_id.

The table follows the loaded ROI identities. Existing biological names and annotation text are preserved by identity when the ROI source changes. Activating a neuron selects its annotation row. Selecting a table row checks and activates the corresponding neuron without clearing other checked IDs. The biological value is also displayed in the neuron list.

The complete navigator is vertically scrollable when the napari dock is shorter than its controls.

Excel operations support .xlsx workbooks. Saving and loading do not apply an implicit +1 or -1 conversion.

Development

Run tests and lint from the repository root:

pixi run pytest -q
pixi run -e excel pytest -q
pixi run ruff check .

The repository uses a src layout. Pure ROI parsing and geometry live in src/napari_worm_neuron_annotator/_roi.py; Qt and napari lifecycle behavior live in src/napari_worm_neuron_annotator/_widget.py.

License

Distributed under the BSD-3-Clause license.