features op• Data kinds: image → feature
• Call: fullseye.apply(img, "xwt_packet_entropy", 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.*
*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
Energy dispersion of wavelet packets (Shannon entropy). Performs a depth-2 wavelet packet decomposition with db1, treats the normalized distribution of the energy (sum of squared coefficients) of each of the 16 leaf subbands as a probability distribution, computes its Shannon entropy, and normalizes it to [0,1] by dividing by log2(16).
a, b are unused. A value closer to 1 indicates that the energy is spread evenly over all frequency bands (complex texture); closer to 0, that it is concentrated in particular bands (simple patterns or flat regions).
• gallery2d_features 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.
xwt_packet_entropy 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_features — py -3.11 examples/gallery2d_features.py
feature as input)features)effective_bit_depth · blob_count · area_frac · count_contours · total_length · vol_count · sk_euler · sk_entropy_feat
*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.