annotate_legend — ANNOTATE `paper` op

• Data kinds: image2d → image2d

• Call: import annotate; annotate.annotate_legend(img, labels, xy, anchor='lt', start=1, radius=7.0, color='emphasis', text_color=None, font_size=12, pad=8, row_gap=4, box_color=None, box_alpha=0.72, border=1, border_color='neutral', scheme='okabe_ito', font_path=None, min_font_size=9, numbers=None) (or opsannotate.get("annotate_legend"))

Usage

Returns an image (image2d): a legend of numbered round markers against their descriptions (the partner of :func:annotate_markers).

> The detailed description below is the original text — the summary and the headings are translated.

箱の高さは閉形式 `2*pad + n*row_h + (n-1)*row_gap(row_h = max(2r, 文字高)`)。

Parameters

----------

labels : sequence of str

各行の説明。

numbers : sequence of str or None

各行のマーカー文字。None なら `start` から連番。

Raises

------

ValueError

labels が空、箱が画像からはみ出す、負の余白。

Detailed usage guide

• figure_annotation family guide

Background guides (the physics and conventions behind this op)

• dataset_conventions — 学習データセット規約の知識 — COCO / YOLO / VOC と外観検査での落とし穴

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• paper_figure — py -3.11 examples/paper_figure.py

Ops the type connects to (they accept `image2d` as input)

text_box · arrow · leader_line · label_points · crosshair · legend_box · color_bar · scale_bar

Same category (`paper`)

annotate_leader_layout · annotate_leader · annotate_markers · annotate_dimension_layout · annotate_dimension · annotate_angle_layout · annotate_angle · annotate_scale_bar_layout

*Provenance: annotate.py — ANNOTATE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

annotate_legend — ANNOTATE paper op