count_channels — 2D `features` op

• Data kinds: color → feature

• Call: fullseye.apply(img, "count_channels", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

• HALCON equivalent: count_channels (the HALCON reference is a useful guide to its meaning and parameters)

count_channels: 入力 → 出力

*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*

Usage

Counts the number of channels in an image. Corresponds to HALCON's `count_channels` (counts the number of channels in an image).

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

`ndim == 3` ならその最後の軸の長さ（チャンネル数）、そうでなければ

（グレースケール扱いで）1 を返す。a, b は未使用。出力は feature

（スカラー 1 個）。

Detailed usage guide

• gallery2d_features family guide

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.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

cfa_to_rgb 0.50 0.50
count_channels 0.50 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_features — py -3.11 examples/gallery2d_features.py

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

identity

Same category (`features`)

blob_count · area_frac · count_contours · total_length · vol_count · sk_euler · sk_entropy_feat · sk_blur_effect

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

count_channels — 2D features op