s6.app.data.filter

Interactively filter entries in one or more StructuredDatasets.

s6.app.data.filter.normalize_datakey(datakey: str) → str

Normalize config-style dotted datakeys into slash-delimited UI keys.

s6.app.data.filter.get_by_datakey(data, datakey)

Retrieve a nested value using a slash- or dot-separated datakey path.

s6.app.data.filter.get_optional_by_datakey(data, datakey)

Retrieve a nested value when present, otherwise return None.

s6.app.data.filter.ensure_vector2d(point) → Vector2D

Convert tuple/list/dict-like points into Vector2D.

s6.app.data.filter.resolve_key_specs(image_keys: Sequence[str] | None, point_keys: Sequence[str] | None, mask_keys: Sequence[str] | None = None) → List[Tuple[str, str, str | None]]

Validate and normalize image, point, and optional mask datakey selections.

s6.app.data.filter.resolve_config_selection(config_path: Path) → Tuple[List[Path], List[Tuple[str, str, str | None]]]

Resolve dataset directories and key specs from a training data config.

s6.app.data.filter.parse_args(argv=None)

Parse CLI arguments for the dataset filter.

s6.app.data.filter.ensure_bgr_image(image)

Return a BGR view of image suitable for overlay drawing.

s6.app.data.filter.overlay_mask(image_bgr: ndarray, mask: ndarray) → ndarray

Blend a segmentation mask onto image_bgr.

s6.app.data.filter.build_zoom_view(image_bgr, point)

Build a zoomed crop centered on point and return zoom metadata.

s6.app.data.filter.render_panel(image, point, image_key, point_key, mask=None, mask_key: str | None = None)

Render one image/point/mask trio as a single annotated panel.

s6.app.data.filter.pad_image(image, target_height, target_width)

Pad image with black pixels to the requested size.

s6.app.data.filter.compose_panels(panels)

Compose panels into a compact grid.

s6.app.data.filter.render_sample(sample, key_specs, idx, total, removed_count, dataset_idx=0, dataset_total=1, dataset_label='')

Render the current dataset entry across all selected sources.

s6.app.data.filter.validate_dataset_dirs(dataset_dirs: Sequence[Path]) → None
s6.app.data.filter.next_dataset_index(lengths: Sequence[int], current: int, direction: int) → int
s6.app.data.filter.main()

Open an interactive viewer to browse and prune dataset entries.