img_to_video — 2D bridge op

• Data kinds: image → video

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

img_to_video: input → output

*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_video: knob a sweep (docs site)

Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):

▸ img_to_video: knob b sweep (docs site)

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

▸ img_to_video: 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).*

Motion (GIF: frames / views / slices in turn. The still figure is the complete one; the GIF is supplementary):

img_to_video: animation

Usage

Turn the image into a T-frame video (T,H,W) translated at constant speed.

Frame t is the input shifted by (dy, dx) = t * step * (sin θ, cos θ) (scipy.ndimage.shift, linear interpolation, borders extended by nearest neighbour). The displacement is known in closed form, so it can be used to cross-check the video family (tb_frame_difference_causal / tb_motion_energy_image / tb_background_subtraction_window …).

• a → step per 1 frame step = 4 * a pixels (2 px/frame at a=0.5).

• b → direction of motion θ = 2π * b (+x at b=0, +y (down) at b=0.25, −x at b=0.5).

• Number of frames T = VIDEO_FRAMES (8). Frame 0 is the input itself.

• Returns: (T, H, W) float64, with the same range as the input (stays [0,1] if [0,1]; linear interpolation does not widen the range).

Note: what moves is the whole frame (a camera pan), not just the objects. The background-subtraction family assumes "a background that does not move", so with a global pan the foreground appears on every pixel.

Detailed usage guide

• gallery2d_bridge 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.

img_to_video 0.50 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_bridge — py -3.11 examples/gallery2d_bridge.py

Ops the type connects to (they accept video as input)

identity · tb_temporal_bandpass · tb_temporal_band_power · tb_temporal_median_window · tb_moving_average_window · tb_background_subtraction_window · tb_frame_difference_causal · tb_exponential_background

Same category (bridge)

img_to_points · img_to_keypoints · img_to_signal · img_to_projection_profile · img_to_counts · img_to_matrix · img_to_volume · img_to_lightfield


*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.