frequency op• Data kinds: image → image
• Call: fullseye.apply(img, "rft_generic", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: rft_generic (the HALCON reference is a useful guide to its meaning and parameters)
A stand-in for the real Fourier transform (real FFT, RFFT). The implementation computes an ordinary complex FFT and returns the absolute value of the real part, `|Re F|`, normalized by its maximum -- it is not the half-size, real-only fast transform (data reduction exploiting symmetry) that HALCON's rft_generic actually computes. a and b are unused.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の `rft_generic`(画像の実数値高速フーリエ変換を計算する演算)に相当する近似 —— 出力される値の意味(実部の大きさの分布)は近いが、アルゴリズムそのものは異なる。
• gallery2d_texture_freq family guide
• 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.
• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
frequency)lowpass · highpass · sk_butterworth · fft_image · power_real · power_byte · phase_rad · highpass_image
*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.