File size: 2,851 Bytes
8420318 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | """Reference (background) frame handling + difference image for GelSight.
GelSight Mini is markerless, so background subtraction is clean (no markers
to occlude). Convention follows Sparsh (Meta, CoRL 2024): a single no-contact
reference frame + signed per-channel difference.
All frames are RGB uint8 (H, W, 3) — the convention returned by the dataset's
video decoder.
"""
from __future__ import annotations
import numpy as np
def get_reference(frames, mode: str = "p01", intensity=None, window: int = 30):
"""Pick a no-contact reference frame from a sequence.
frames: (T, H, W, 3) uint8 OR a callable i->frame for lazy access with
an explicit `intensity` array.
mode:
"first" -> frames[0]
"p01" -> the 1st-percentile-intensity (quietest) frame; needs
`intensity` (T,) array of per-frame contact intensity,
else computes a cheap proxy = mean abs deviation from
the temporal median.
"running_avg" -> mean of the `window` lowest-intensity frames.
Returns an (H, W, 3) uint8 reference.
"""
arr = np.asarray(frames)
T = arr.shape[0]
if mode == "first":
return arr[0].copy()
if intensity is None:
med = np.median(arr.reshape(T, -1).astype(np.float32), axis=0)
intensity = np.abs(arr.reshape(T, -1).astype(np.float32) - med).mean(axis=1)
intensity = np.asarray(intensity, np.float32)
if mode == "p01":
thr = np.percentile(intensity, 1)
idx = int(np.where(intensity <= thr)[0][0]) if (intensity <= thr).any() else int(intensity.argmin())
return arr[idx].copy()
if mode == "running_avg":
k = min(window, T)
order = np.argsort(intensity)[:k]
return arr[order].mean(axis=0).round().astype(np.uint8)
raise ValueError(f"unknown reference mode: {mode}")
def difference(frame, reference, signed: bool = True):
"""Sparsh-style difference image.
signed=True -> (frame - ref)/255 + 0.5, clipped to [0,1], scaled to uint8.
Mid-gray = no change; preserves direction of deformation.
signed=False -> |frame - ref| as uint8 (magnitude only).
frame/reference: (H, W, 3) uint8. Returns (H, W, 3) uint8.
"""
f = frame.astype(np.float32)
r = reference.astype(np.float32)
if signed:
d = (f - r) / 255.0 + 0.5
return (np.clip(d, 0, 1) * 255).astype(np.uint8)
return np.clip(np.abs(f - r), 0, 255).astype(np.uint8)
def l2_diff(frame, reference):
"""Per-pixel L2 distance across RGB channels (H, W) float32.
This is the quantity the dataset's contact scalars are built on:
d[h,w] = ||frame[h,w,:] - ref[h,w,:]||_2.
"""
return np.sqrt(((frame.astype(np.float32) - reference.astype(np.float32)) ** 2).sum(axis=2))
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