bridge op• Data kinds: image → beatcube
• Call: fullseye.apply(img, "img_to_beatcube", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ img_to_beatcube: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ img_to_beatcube: knob b sweep (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ img_to_beatcube: other inputs (docs site)
*The 4th column is a colour (H,W,3) input. This op handles colour without crossing channels (it does not convolve the colour channel as a third spatial axis).*
Read the bright spots of the image as FMCW radar targets (range = column, velocity = row) and synthesise the complex beat cube (A,C,S).
> The detailed description below is the original text — the summary and the headings are translated.
平滑化(σ=2)した画像の局所極大を値の降順に `K` 個拾い、各点を標的にする:
`range_m = 2 + 30 * col / W、velocity_ms = 15 * (2 * row / H - 1)`、
振幅 = 画素値。前方モデルは台帳の `fmcw_beat_simulate(rangedoppler`)
そのもので、`n_samples = 64、n_chirps = 32、n_antennas = 4`(素子間隔は
既定の半波長、標的はすべて正面 = 到来角 0°)、その他は
同関数の既定(標本化 10 MHz、掃引 20 THz/s、チャープ周期 50 µs、波長 3.89 mm)。
この既定では 距離は 0〜37.5 m、速度は ±19.5 m/s が曖昧さの無い範囲 で、
上の写像はその内側に収まる。
• `a → 複素白色雑音の σ = 0.5 * a`(a=0 で無雑音)。
• `b → 標的数 K = 1 + int(b * 6)`(b=0.5 で 4。極大が足りなければその数)。
• 返り値: `(4, 32, 64) complex128。tb_range_doppler_map` で 2-D FFT すると
標的ごとの峰が「列 → 距離ビン、行 → ドップラービン」に立ち、
`tb_beamform_delay_sum` は 4 素子で到来角 0° の峰を返す。
• 乱数 seed は 0 固定(決定的)。速度の符号は `fmcw_beat_simulate` の規約
(正 = 遠ざかる)。
• gallery2d_bridge 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.
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.
img_to_beatcube 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_bridge — py -3.11 examples/gallery2d_bridge.py
beatcube as input)identity · tb_fmcw_window_apply · tb_range_doppler_map · tb_fmcw_range_profile · tb_beamform_delay_sum
bridge)img_to_points · img_to_keypoints · img_to_signal · img_to_projection_profile · img_to_counts · img_to_matrix · img_to_video · img_to_volume
*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.