feat(lena-hands): exp09 graded cross-digit finger weights + honest tear metrics

The exp05 verdict ("weights alone cannot clear the bar on this mesh") was
measured against a hard partition that was itself causing much of the tearing.
exp01-exp05 gave every vert to exactly ONE digit -- 08_finger_weights.py had an
explicit `elif lo in FING: continue  # other digit: hard wall` -- which
guarantees the fused inter-digit bridges tear by the full finger separation,
because a single edge ring absorbs the whole gap.

Replace that with graded blending (WEB_BLEND_R0): a vert's fraction toward its
nearest other digit ramps 0 -> 0.5 as r = d_own/(d_own+d_other) goes 0.35 -> 0.5,
so both sides of the equidistance valley reach 50/50 and the field is continuous
across the boundary. Applied after the smoother (whose hard wall would erode beta
exactly where it must survive) and evaluated in the neighbour digit's own
arc-length frame. WEB_BLEND_SKIP excludes the thumb: its transform is opposition,
not curl, so its frame does not correspond to a finger's.

Measured against an identical baseline (same input, blend the only variable),
real tears (>=1mm rest length) drop 23-60% with NO regression on flat, the pose
that ships: fist_r 1178 -> 530, grip_r 561 -> 222, fist_l 979 -> 633,
grip_l 420 -> 322; total >5x 2487 -> 1307; p99.9 better on every pose;
flat unchanged at 0/1. fin_bones confirms the mechanism rather than just the
count -- the middle<->ring and pinky<->ring families leave the top classes while
the thumb/palm ones are untouched to the edge (182 -> 182, 148 -> 148).

This does NOT make fist/grip shippable: 222-633 real tears still reads as a
destroyed hand in clay renders, and the residual is now ~53% thumb-pad-fused-to
-palm, which is topology and needs mesh surgery or the v02 rebake. Flat and
relaxed are the shippable poses; fist/grip belong to the morph lane for now.

Also here:
- README: the solver's input is v02/..._exp03.glb, NOT exp01. exp01 is pre-hand
  -fit (converter steps 2b/2c); its finger groups sit on the wrist and overlap
  the real finger by 1.6cm, so a solve from it silently zeroes every _02/_03 bone
  -- rigid stick fingers and a torn flat -- while weight sums stay 1.0 and every
  assert passes. Cost three wasted bakes and one false "the solver regressed".
- Seed assert demanded >=100 seeds while the radius loop caps at
  SEED_AXIS_R_MAX, which left pinky (88 seeds at 16mm) can never satisfy; the two
  constants were mutually unsatisfiable. Now >=60, and it is documented as a
  sanity gate rather than a quality bar.
- Detwist poses tested at last: real but marginal (fist_r 38.7x -> 28.7x,
  grip_r 30.0x -> 17.3x, left hand flat). A knob, not a fix.
- edge_stretch_cmp.py / skin_bone_territory.py / handpose_trim_hand_obj.py:
  judge tears by rest length and absolute posed growth, not raw ratio; audit
  whether a bone owns any verts at all (thumb_01 owns ZERO in exp05); and trim
  an arm-sized skin dump to the hand before rendering.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
2026-08-18 11:33:15 -07:00
parent 3f335ee2d7
commit cf336f3b5b
28 changed files with 3285 additions and 14 deletions
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"""Diagnose cross-midline finger bindings: for every offending ref, compare the lever arm
to the WRONG joint against the lever to its MIRRORED counterpart, so we can tell whether a
straight _r <-> _l joint remap is geometrically correct (small mirrored lever) or would tear
(vert nowhere near the mirrored bone either).
Also reports each offending vert's full influence list, and the nearest correct finger joint.
usage: crosshand_diagnose.py body.glb
"""
import json, struct, sys, math
from pathlib import Path
from collections import Counter, defaultdict
FING = ("thumb", "index", "middle", "ring", "pinky")
def read_glb(p):
d = Path(p).read_bytes()
length = struct.unpack_from("<I", d, 8)[0]
off = 12
g = b_ = None
while off < length:
clen, ct = struct.unpack_from("<II", d, off)
off += 8
if ct == 0x4E4F534A:
g = json.loads(d[off:off + clen])
else:
b_ = d[off:off + clen]
off += clen
return g, b_
def acc(g, b, i):
a = g["accessors"][i]
bv = g["bufferViews"][a["bufferView"]]
nc = {"SCALAR": 1, "VEC2": 2, "VEC3": 3, "VEC4": 4, "MAT4": 16}[a["type"]]
fmt = {5121: "B", 5123: "H", 5125: "I", 5126: "f"}[a["componentType"]]
size = struct.calcsize(fmt) * nc
stride = bv.get("byteStride") or size
off = bv.get("byteOffset", 0) + a.get("byteOffset", 0)
return [struct.unpack_from("<%d%s" % (nc, fmt), b, off + k * stride)
for k in range(a["count"])], a["componentType"]
def quat_mat(q):
x, y, z, w = q
return [[1 - 2 * (y * y + z * z), 2 * (x * y - z * w), 2 * (x * z + y * w)],
[2 * (x * y + z * w), 1 - 2 * (x * x + z * z), 2 * (y * z - x * w)],
[2 * (x * z - y * w), 2 * (y * z + x * w), 1 - 2 * (x * x + y * y)]]
def node_local(nd):
t = nd.get("translation", [0, 0, 0])
r = nd.get("rotation", [0, 0, 0, 1])
s = nd.get("scale", [1, 1, 1])
R = quat_mat(r)
return [[R[i][j] * s[j] for j in range(3)] + [t[i]] for i in range(3)] + [[0, 0, 0, 1]]
def matmul(A, B):
return [[sum(A[i][k] * B[k][j] for k in range(4)) for j in range(4)] for i in range(4)]
def global_mats(g):
loc = [node_local(nd) for nd in g["nodes"]]
parent = {}
for i, nd in enumerate(g["nodes"]):
for c in nd.get("children", []):
parent[c] = i
memo = {}
def gm(i):
if i in memo:
return memo[i]
m = loc[i]
p = parent.get(i)
if p is not None:
m = matmul(gm(p), m)
memo[i] = m
return m
return [gm(i) for i in range(len(g["nodes"]))]
def mirror_name(n):
if n.endswith("_r"):
return n[:-2] + "_l"
if n.endswith("_l"):
return n[:-2] + "_r"
return None
path = sys.argv[1]
g, b = read_glb(path)
names = [nd.get("name", "") for nd in g["nodes"]]
GM = global_mats(g)
mesh = g["meshes"][0]
prim = mesh["primitives"][0]
att = prim["attributes"]
skin_idx = next(nd.get("skin") for nd in g["nodes"] if nd.get("mesh") == 0 and "skin" in nd)
joints = g["skins"][skin_idx]["joints"]
jname = [names[j] for j in joints]
jpos = {jname[k]: (GM[j][0][3], GM[j][1][3], GM[j][2][3]) for k, j in enumerate(joints)}
P, _ = acc(g, b, att["POSITION"])
J, _ = acc(g, b, att["JOINTS_0"])
W, wt = acc(g, b, att["WEIGHTS_0"])
wsc = 1.0 if wt == 5126 else (1 / 255 if wt == 5121 else 1 / 65535)
# hand-bone anchors, to describe where verts sit
print(f"== {Path(path).name} ==")
for hb in ("hand_l", "hand_r", "middle_01_l", "middle_01_r", "middle_03_l", "middle_03_r"):
if hb in jpos:
p = jpos[hb]
print(f" {hb:14s} rest pos = ({p[0]*100:7.1f}, {p[1]*100:7.1f}, {p[2]*100:7.1f}) cm")
bad = []
for vi, (p, jrow, wrow) in enumerate(zip(P, J, W)):
for j, w in zip(jrow, wrow):
w *= wsc
if w <= 0.001:
continue
n = jname[j]
nl = n.lower()
if not any(t in nl for t in FING):
continue
if (nl.endswith("_r") and p[0] > 0.02) or (nl.endswith("_l") and p[0] < -0.02):
bad.append((vi, n, w, p))
print(f"\n cross-midline finger refs: {len(bad)}")
vids = sorted({v for v, _, _, _ in bad})
print(f" distinct verts affected : {len(vids)} (index range {min(vids)}..{max(vids)})")
# lever comparison: wrong joint vs mirrored joint vs nearest correct-side finger joint
print(f"\n {'joint':16s} {'n':>5s} {'lever_wrong':>12s} {'lever_mirror':>13s} {'nearest_correct'}")
groups = defaultdict(list)
for vi, n, w, p in bad:
groups[n].append((vi, w, p))
for n in sorted(groups):
rows = groups[n]
mn = mirror_name(n)
lw = [math.dist(p, jpos[n]) * 100 for _, _, p in rows]
lm = [math.dist(p, jpos[mn]) * 100 for _, _, p in rows] if mn in jpos else [float("nan")]
# nearest correct-side finger joint for a sample vert
side = "_l" if rows[0][2][0] > 0 else "_r"
cand = [(math.dist(rows[0][2], jpos[k]) * 100, k) for k in jpos
if any(t in k.lower() for t in FING) and k.endswith(side)]
cand.sort()
print(f" {n:16s} {len(rows):5d} {sum(lw)/len(lw):9.1f}cm {sum(lm)/len(lm):10.1f}cm "
f" {cand[0][1]} @ {cand[0][0]:.1f}cm")
# full influence list for a few offenders
print("\n sample offending verts (full influence list):")
for vi in vids[:6]:
p = P[vi]
infl = []
for j, w in zip(J[vi], W[vi]):
w *= wsc
if w > 0.001:
infl.append(f"{jname[j]}={w:.3f}")
print(f" v{vi} pos=({p[0]*100:6.1f},{p[1]*100:6.1f},{p[2]*100:6.1f})cm {' '.join(infl)}")
# how many offending verts are FULLY (>0.99) bound to a wrong joint
full = sum(1 for vi, n, w, p in bad if w > 0.99)
print(f"\n refs at weight > 0.99 (rigid, no blend to soften): {full}")
# what fraction of total left-hand-region verts are affected
hl = jpos.get("hand_l")
if hl:
near = [vi for vi, p in enumerate(P) if math.dist(p, hl) < 0.20]
aff = set(vids) & set(near)
print(f" verts within 20cm of hand_l: {len(near)}; of those affected: {len(aff)}")
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"""Edge-stretch fin detector (pure python): posed OBJ edge lengths vs rest OBJ."""
import sys, os, math
def load_obj(path):
vs, faces = [], []
with open(path) as f:
for line in f:
if line.startswith('v '):
p = line.split()
vs.append((float(p[1]), float(p[2]), float(p[3])))
elif line.startswith('f '):
idx = [int(tok.split('/')[0]) - 1 for tok in line.split()[1:]]
for i in range(1, len(idx) - 1):
faces.append((idx[0], idx[i], idx[i + 1]))
return vs, faces
def edge_set(faces):
es = set()
for a, b, c in faces:
for u, v in ((a, b), (b, c), (c, a)):
es.add((u, v) if u < v else (v, u))
return sorted(es)
def dist(p, q):
return math.sqrt((p[0]-q[0])**2 + (p[1]-q[1])**2 + (p[2]-q[2])**2)
d = sys.argv[1]
for hand in ('l', 'r'):
rest_v, rest_f = load_obj(os.path.join(d, f'rest_hand_{hand}.obj'))
edges = edge_set(rest_f)
rest_len = [dist(rest_v[a], rest_v[b]) for a, b in edges]
for pose in ('flat', 'fist', 'grip'):
v, _ = load_obj(os.path.join(d, f'{pose}_hand_{hand}.obj'))
if len(v) != len(rest_v):
print(f'{pose}_hand_{hand}: VERTEX COUNT MISMATCH {len(v)} vs {len(rest_v)}')
continue
ratios = []
for (a, b), rl in zip(edges, rest_len):
if rl <= 1e-9:
continue
ratios.append((dist(v[a], v[b]) / rl, a, b))
ratios.sort(key=lambda t: t[0])
n = len(ratios)
mx = ratios[-1][0]
p999 = ratios[int(n * 0.999)][0]
n2 = sum(1 for r, _, _ in ratios if r > 2)
n3 = sum(1 for r, _, _ in ratios if r > 3)
n5 = sum(1 for r, _, _ in ratios if r > 5)
print(f'{pose}_hand_{hand}: edges={n} max={mx:.2f}x p99.9={p999:.2f}x >2x={n2} >3x={n3} >5x={n5}')
for r, a, b in ratios[-min(max(n3, 3), 8):][::-1]:
pa = [c * 100 for c in v[a]]
rl = dist(rest_v[a], rest_v[b]) * 100
print(f' {r:7.1f}x rest {rl:5.2f}cm -> {r*rl:7.1f}cm at posed ({pa[0]:.1f}, {pa[1]:.1f}, {pa[2]:.1f}) cm')
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"""Edge-stretch comparison across OBJ dirs, with a rest-length split.
usage: stretch_cmp.py <rest_dir> <label>=<dir> [<label>=<dir> ...]
Rest OBJs (rest_hand_l/r.obj) come from <rest_dir>; every compared dir must share the
body's vertex order. Reports, per pose and hand: max / p99.9 / >2x / >5x over ALL edges,
then the subset that is real geometry (>=1mm rest length) and the subset that is
VISIBLE (posed length >=1cm) — the count that decides whether a render shows a needle.
"""
import math
import os
import sys
def load_obj(path):
vs, faces = [], []
with open(path) as f:
for line in f:
if line.startswith("v "):
p = line.split()
vs.append((float(p[1]), float(p[2]), float(p[3])))
elif line.startswith("f "):
idx = [int(t.split("/")[0]) - 1 for t in line.split()[1:]]
for i in range(1, len(idx) - 1):
faces.append((idx[0], idx[i], idx[i + 1]))
return vs, faces
def edge_set(faces):
es = set()
for a, b, c in faces:
for u, v in ((a, b), (b, c), (c, a)):
es.add((u, v) if u < v else (v, u))
return sorted(es)
def dist(p, q):
return math.sqrt(sum((p[i] - q[i]) ** 2 for i in range(3)))
rest_dir = sys.argv[1]
cols = [a.split("=", 1) for a in sys.argv[2:]]
for hand in ("l", "r"):
rest_v, rest_f = load_obj(os.path.join(rest_dir, f"rest_hand_{hand}.obj"))
edges = edge_set(rest_f)
rest_len = [dist(rest_v[a], rest_v[b]) for a, b in edges]
print(f"\n=== hand_{hand} ({len(rest_v)} verts, {len(edges)} edges) ===")
print(f"{'pose / build':22s} {'max':>8s} {'p99.9':>7s} {'>2x':>6s} {'>5x':>6s}"
f" {'>5x real':>9s} {'>=1cm':>7s}")
for pose in ("flat", "fist", "grip"):
for label, d in cols:
f = os.path.join(d, f"{pose}_hand_{hand}.obj")
if not os.path.exists(f):
continue
v, _ = load_obj(f)
if len(v) != len(rest_v):
print(f"{pose+' '+label:22s} VERT COUNT MISMATCH {len(v)} vs {len(rest_v)}")
continue
rs = []
gt5 = gt2 = real5 = vis = 0
for (a, b), rl in zip(edges, rest_len):
if rl <= 1e-9:
continue
lq = dist(v[a], v[b])
r = lq / rl
rs.append(r)
if r > 2:
gt2 += 1
if r > 5:
gt5 += 1
if rl >= 0.001:
real5 += 1
if lq >= 0.01:
vis += 1
rs.sort()
print(f"{pose+' '+label:22s} {rs[-1]:7.1f}x {rs[int(len(rs)*0.999)]:6.2f}x"
f" {gt2:6d} {gt5:6d} {real5:9d} {vis:7d}")
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"""Classify torn edges (posed stretch >5x) by the dominant joint of each endpoint.
usage: fin_bones.py posed.glb"""
import json, struct, sys, math
from pathlib import Path
from collections import Counter
def read_glb(path):
d = Path(path).read_bytes()
length = struct.unpack_from("<I", d, 8)[0]
off = 12; g = None; b = None
while off < length:
clen, ct = struct.unpack_from("<II", d, off); off += 8
if ct == 0x4E4F534A: g = json.loads(d[off:off+clen])
else: b = d[off:off+clen]
off += clen
return g, b
def acc(g, b, i):
a = g["accessors"][i]; bv = g["bufferViews"][a["bufferView"]]
nc = {"SCALAR":1,"VEC2":2,"VEC3":3,"VEC4":4,"MAT4":16}[a["type"]]
fmt = {5121:"B",5123:"H",5125:"I",5126:"f"}[a["componentType"]]
size = struct.calcsize(fmt)*nc; stride = bv.get("byteStride") or size
off = bv.get("byteOffset",0)+a.get("byteOffset",0)
return [struct.unpack_from("<%d%s"%(nc,fmt), b, off+i*stride) for i in range(a["count"])], a["componentType"]
def quat_mat(q):
x,y,z,w = q
return [[1-2*(y*y+z*z),2*(x*y-z*w),2*(x*z+y*w)],
[2*(x*y+z*w),1-2*(x*x+z*z),2*(y*z-x*w)],
[2*(x*z-y*w),2*(y*z+x*w),1-2*(x*x+y*y)]]
def node_local(nd):
t = nd.get("translation",[0,0,0]); r = nd.get("rotation",[0,0,0,1]); s = nd.get("scale",[1,1,1])
R = quat_mat(r)
M = [[R[i][j]*s[j] for j in range(3)]+[t[i]] for i in range(3)]
return M+[[0,0,0,1]]
def matmul(A,B):
return [[sum(A[i][k]*B[k][j] for k in range(4)) for j in range(4)] for i in range(4)]
g, b = read_glb(sys.argv[1])
names = [nd.get("name","") for nd in g["nodes"]]
loc = [node_local(nd) for nd in g["nodes"]]
parent = {}
for i,nd in enumerate(g["nodes"]):
for c in nd.get("children",[]): parent[c] = i
memo = {}
def gm(i):
if i in memo: return memo[i]
m = loc[i] if i not in parent else matmul(gm(parent[i]), loc[i])
memo[i] = m; return m
G = [gm(i) for i in range(len(g["nodes"]))]
skin = g["skins"][0]; joints = skin["joints"]
ibm,_ = acc(g,b,skin["inverseBindMatrices"])
def m16(row): return [[row[c*4+r] for c in range(4)] for r in range(4)]
JM = [matmul(G[joints[j]], m16(ibm[j])) for j in range(len(joints))]
prim = g["meshes"][0]["primitives"][0]
P,_ = acc(g,b,prim["attributes"]["POSITION"])
J,_ = acc(g,b,prim["attributes"]["JOINTS_0"])
W,wt = acc(g,b,prim["attributes"]["WEIGHTS_0"])
wsc = 1.0 if wt==5126 else (1/255 if wt==5121 else 1/65535)
IDX,_ = acc(g,b,prim["indices"])
idx = [i[0] for i in IDX]
def skin_pos(vi):
p = P[vi]; x=y=z=0.0
for j,w in zip(J[vi],W[vi]):
w*=wsc
if w<=0: continue
M=JM[j]
x+=w*(M[0][0]*p[0]+M[0][1]*p[1]+M[0][2]*p[2]+M[0][3])
y+=w*(M[1][0]*p[0]+M[1][1]*p[1]+M[1][2]*p[2]+M[1][3])
z+=w*(M[2][0]*p[0]+M[2][1]*p[1]+M[2][2]*p[2]+M[2][3])
return (x,y,z)
def dom(vi):
best, bw = None, 0
for j,w in zip(J[vi],W[vi]):
w*=wsc
if w>bw: bw, best = w, j
return names[joints[best]] if best is not None else "?"
edges = set()
for t in range(0, len(idx), 3):
a_,b_,c_ = idx[t], idx[t+1], idx[t+2]
for u,v in ((a_,b_),(b_,c_),(c_,a_)):
edges.add((u,v) if u<v else (v,u))
pos_cache = {}
def sp(vi):
if vi not in pos_cache: pos_cache[vi] = skin_pos(vi)
return pos_cache[vi]
pairs = Counter(); n_bad = 0; maxr = 0
for u,v in edges:
rl = math.dist(P[u], P[v])
if rl <= 1e-9: continue
# cheap prefilter: only edges where an endpoint is finger/hand weighted
dn_u, dn_v = dom(u), dom(v)
lu, lv = dn_u.lower(), dn_v.lower()
keys = ("thumb","index","middle","ring","pinky","hand","lower_arm","wrist")
if not any(k in lu or k in lv for k in keys): continue
r = math.dist(sp(u), sp(v)) / rl
if r > 5:
n_bad += 1; maxr = max(maxr, r)
pairs[tuple(sorted((dn_u, dn_v)))] += 1
print(f"edges>5x: {n_bad} max stretch {maxr:.0f}x")
for (a_,b_), n in pairs.most_common(20):
print(f" {n:5d} {a_} <-> {b_}")
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"""For each finger bone, report how much geometry it actually OWNS (verts where it is the
dominant influence) and where that geometry sits. On a two-finger hand rig the five-finger
bone set is present but several chains own nothing, or several chains share one fused mass.
usage: hand_bone_ownership.py body.glb [side l|r]
"""
import json, struct, sys, math
from pathlib import Path
from collections import defaultdict
FING = ("thumb", "index", "middle", "ring", "pinky")
side = sys.argv[2] if len(sys.argv) > 2 else None
def read_glb(p):
d = Path(p).read_bytes()
length = struct.unpack_from("<I", d, 8)[0]
off = 12
g = b_ = None
while off < length:
clen, ct = struct.unpack_from("<II", d, off)
off += 8
if ct == 0x4E4F534A:
g = json.loads(d[off:off + clen])
else:
b_ = d[off:off + clen]
off += clen
return g, b_
def acc(g, b, i):
a = g["accessors"][i]
bv = g["bufferViews"][a["bufferView"]]
nc = {"SCALAR": 1, "VEC2": 2, "VEC3": 3, "VEC4": 4, "MAT4": 16}[a["type"]]
fmt = {5121: "B", 5123: "H", 5125: "I", 5126: "f"}[a["componentType"]]
size = struct.calcsize(fmt) * nc
stride = bv.get("byteStride") or size
off = bv.get("byteOffset", 0) + a.get("byteOffset", 0)
return [struct.unpack_from("<%d%s" % (nc, fmt), b, off + k * stride)
for k in range(a["count"])], a["componentType"]
g, b = read_glb(sys.argv[1])
names = [nd.get("name", "") for nd in g["nodes"]]
prim = g["meshes"][0]["primitives"][0]
att = prim["attributes"]
skin = next(nd["skin"] for nd in g["nodes"] if nd.get("mesh") == 0 and "skin" in nd)
joints = g["skins"][skin]["joints"]
jname = [names[j] for j in joints]
P, _ = acc(g, b, att["POSITION"])
J, _ = acc(g, b, att["JOINTS_0"])
W, wt = acc(g, b, att["WEIGHTS_0"])
wsc = 1.0 if wt == 5126 else (1 / 255 if wt == 5121 else 1 / 65535)
own = defaultdict(list)
for vi, (p, jrow, wrow) in enumerate(zip(P, J, W)):
best = (0.0, None)
for j, w in zip(jrow, wrow):
w *= wsc
if w > best[0]:
best = (w, jname[j])
if best[1] and any(t in best[1].lower() for t in FING):
if side and not best[1].lower().endswith("_" + side):
continue
own[best[1]].append(p)
print(f"{Path(sys.argv[1]).name} dominant-owner geometry per finger bone"
f"{' (side ' + side + ')' if side else ''}\n")
print(f" {'bone':20s} {'verts':>7s} {'z-centre':>9s} {'z-span':>8s} {'x-centre':>9s}")
for fam in FING:
rows = [(n, v) for n, v in own.items() if fam in n.lower()]
if not rows:
print(f" {fam:20s} {'0':>7s} -- owns no geometry --")
continue
for n in sorted(r[0] for r in rows):
ps = own[n]
zc = sum(p[2] for p in ps) / len(ps) * 100
zs = (max(p[2] for p in ps) - min(p[2] for p in ps)) * 100
xc = sum(p[0] for p in ps) / len(ps) * 100
print(f" {n:20s} {len(ps):7d} {zc:8.1f}cm {zs:7.1f}cm {xc:8.1f}cm")
print()
tot = sum(len(v) for v in own.values())
print(f" total finger-owned verts: {tot}")
+61
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"""Bake a hand-pose JSON into a body GLB by rewriting finger node rest rotations.
IBMs untouched -> mesh deforms to the pose. usage: bake_preview.py body.glb pose.json out.glb"""
import json, struct, sys
from pathlib import Path
body, posef, out = sys.argv[1:4]
data = Path(body).read_bytes()
length = struct.unpack_from("<I", data, 8)[0]
off = 12
chunks = []
gltf = None
while off < length:
clen, ctype = struct.unpack_from("<II", data, off)
off += 8
if ctype == 0x4E4F534A:
gltf = json.loads(data[off:off+clen].decode("utf-8"))
chunks.append([ctype, None])
else:
chunks.append([ctype, data[off:off+clen]])
off += clen
pose = json.loads(Path(posef).read_text())["bones"]
byname = {nd.get("name"): nd for nd in gltf["nodes"]}
canon = None
if len(sys.argv) > 4: # canonical-rest GLB: apply pose as rest-relative delta
cdata = Path(sys.argv[4]).read_bytes()
clen2 = struct.unpack_from("<I", cdata, 12)[0]
cg = json.loads(cdata[20:20+clen2].decode("utf-8"))
canon = {nd.get("name"): nd.get("rotation", [0, 0, 0, 1]) for nd in cg["nodes"]}
def qmul(a, b):
ax, ay, az, aw = a; bx, by, bz, bw = b
return [aw*bx + ax*bw + ay*bz - az*by,
aw*by - ax*bz + ay*bw + az*bx,
aw*bz + ax*by - ay*bx + az*bw,
aw*bw - ax*bx - ay*by - az*bz]
n = 0
for bone, quat in pose.items():
if bone in byname:
if canon is not None:
cr = canon.get(bone, [0, 0, 0, 1])
delta = qmul([-cr[0], -cr[1], -cr[2], cr[3]], quat) # canon_rest^-1 * pose
body_rest = byname[bone].get("rotation", [0, 0, 0, 1])
quat = qmul(body_rest, delta)
byname[bone]["rotation"] = quat
n += 1
# strip animations so nothing overrides the pose
gltf.pop("animations", None)
js = json.dumps(gltf, separators=(",", ":")).encode("utf-8")
js += b" " * ((4 - len(js) % 4) % 4)
body_out = b""
for ctype, payload in chunks:
if ctype == 0x4E4F534A:
payload = js
body_out += struct.pack("<II", len(payload), ctype) + payload
hdr = struct.pack("<III", 0x46546C67, 2, 12 + len(body_out))
Path(out).write_bytes(hdr + body_out)
print(f"baked {n}/{len(pose)} bones -> {out}")
+71
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"""Strip axial roll (twist about the bone axis) from a hand-pose JSON, keeping the curl.
The pose delta vs the body's rest is swing-twist decomposed per bone; the twist factor is
dropped and the pose rebuilt as rest*swing. Thumb chains are left untouched (their roll is
functional opposition). usage: handpose_detwist.py body.glb pose_in.json pose_out.json"""
import json, math, struct, sys
from pathlib import Path
body, pose_in, pose_out = sys.argv[1:4]
data = Path(body).read_bytes()
jlen = struct.unpack_from("<I", data, 12)[0]
gltf = json.loads(data[20:20 + jlen].decode("utf-8"))
nodes = gltf["nodes"]
byname = {n.get("name"): i for i, n in enumerate(nodes)}
def qmul(a, b):
ax, ay, az, aw = a
bx, by, bz, bw = b
return [aw * bx + ax * bw + ay * bz - az * by,
aw * by - ax * bz + ay * bw + az * bx,
aw * bz + ax * by - ay * bx + az * bw,
aw * bw - ax * bx - ay * by - az * bz]
def qinv(q):
return [-q[0], -q[1], -q[2], q[3]]
def qnorm(q):
m = math.sqrt(sum(v * v for v in q))
return [v / m for v in q]
def bone_axis(i):
for c in nodes[i].get("children", []):
t = nodes[c].get("translation")
if t:
m = math.sqrt(sum(v * v for v in t))
if m > 1e-8:
return [v / m for v in t]
return None
pose = json.loads(Path(pose_in).read_text())["bones"]
out = {}
report = []
for name, p in pose.items():
i = byname.get(name)
if i is None or name.startswith("thumb"):
out[name] = p
continue
a = bone_axis(i)
if a is None: # leaf tips: twist is invisible, keep as-is
out[name] = p
continue
r = nodes[i].get("rotation", [0, 0, 0, 1])
d = qmul(qinv(r), p) # delta in the bone's rest-local frame
dot = d[0] * a[0] + d[1] * a[1] + d[2] * a[2]
twist = qnorm([dot * a[0], dot * a[1], dot * a[2], d[3]])
swing = qmul(d, qinv(twist))
out[name] = [round(v, 6) for v in qnorm(qmul(r, swing))]
deg = 2 * math.degrees(math.atan2(abs(dot), abs(d[3])))
if deg > 1.0:
report.append((deg, name))
Path(pose_out).write_text(json.dumps({"bones": out}, indent=1))
report.sort(reverse=True)
print("wrote %s (%d bones, thumbs untouched)" % (pose_out, len(out)))
for deg, name in report[:6]:
print(" stripped %5.1f deg %s" % (deg, name))
+99
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"""Extract a hand pose (40 finger-bone quaternions) from a GLB clip at a chosen frame,
report per-bone curl (deviation from skeleton rest), optionally dump JSON.
usage: python extract_pose.py <glb> <animName> [--frame N | --max-curl] [--dump out.json]
python extract_pose.py <glb> --rest --dump out.json (rest pose itself)
"""
import json, struct, sys, math
from pathlib import Path
FINGER_TOKENS = ("thumb", "index", "middle", "ring", "pinky")
def read_glb(path):
data = Path(path).read_bytes()
magic, ver, length = struct.unpack_from("<III", data, 0)
off = 12
gltf = None; binc = None
while off < length:
clen, ctype = struct.unpack_from("<II", data, off)
off += 8
chunk = data[off:off+clen]
if ctype == 0x4E4F534A: gltf = json.loads(chunk.decode("utf-8"))
elif ctype == 0x004E4942: binc = chunk
off += clen
return gltf, binc
def acc_data(gltf, binc, idx):
acc = gltf["accessors"][idx]
bv = gltf["bufferViews"][acc["bufferView"]]
n = {"SCALAR":1, "VEC3":3, "VEC4":4}[acc["type"]]
off = bv.get("byteOffset", 0) + acc.get("byteOffset", 0)
vals = struct.unpack_from("<%d%s" % (acc["count"]*n, "f"), binc, off)
return [vals[i*n:(i+1)*n] for i in range(acc["count"])]
def qangle(a, b):
d = min(1.0, abs(sum(x*y for x, y in zip(a, b))))
return 2*math.degrees(math.acos(d))
def main():
glb = sys.argv[1]
gltf, binc = read_glb(glb)
nodes = gltf["nodes"]
names = [nd.get("name", f"n{i}") for i, nd in enumerate(nodes)]
finger_idx = {i: names[i] for i, nd in enumerate(nodes)
if any(t in names[i].lower() for t in FINGER_TOKENS)}
rest = {i: tuple(nodes[i].get("rotation", [0, 0, 0, 1])) for i in finger_idx}
dump = None
if "--dump" in sys.argv:
dump = sys.argv[sys.argv.index("--dump")+1]
if "--rest" in sys.argv:
pose = {names[i]: list(rest[i]) for i in finger_idx}
label = "REST"
else:
aname = sys.argv[2]
anim = next(a for a in gltf["animations"] if a.get("name") == aname)
# collect finger rotation samplers
tracks = {}
times_ref = None
for ch in anim["channels"]:
t = ch["target"]
if t.get("path") != "rotation" or t["node"] not in finger_idx: continue
samp = anim["samplers"][ch["sampler"]]
quats = acc_data(gltf, binc, samp["output"])
tracks[t["node"]] = quats
times_ref = acc_data(gltf, binc, samp["input"])
nframes = min(len(q) for q in tracks.values())
if "--max-curl" in sys.argv:
best, bestf = -1, 0
for f in range(nframes):
curl = sum(qangle(tracks[i][f], rest[i]) for i in tracks)
if curl > best: best, bestf = curl, f
frame = bestf
elif "--frame" in sys.argv:
frame = int(sys.argv[sys.argv.index("--frame")+1])
else:
frame = 0
t = times_ref[min(frame, len(times_ref)-1)][0] if times_ref else 0
pose = {names[i]: list(tracks[i][frame]) for i in tracks}
# fill missing finger bones from rest
for i in finger_idx:
pose.setdefault(names[i], list(rest[i]))
label = f"{aname} frame {frame} (t={t:.2f}s)"
# curl report per finger chain (sum of deviations from rest), L hand only for brevity
print(f"pose: {label} ({len(pose)} bones)")
for hand in ("_l", "_r"):
parts = []
for fing in ("thumb", "index", "middle", "ring", "pinky"):
tot = sum(qangle(pose[n], rest[i]) for i, n in finger_idx.items()
if n.startswith(fing) and n.endswith(hand))
parts.append(f"{fing} {tot:.0f}")
print(f" {hand}: curl-vs-rest deg " + " ".join(parts))
if dump:
Path(dump).write_text(json.dumps({"source": f"{Path(glb).name}:{label}",
"bones": pose}, indent=1))
print("dumped ->", dump)
main()
+59
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"""Clay-render each OBJ in a directory, 3 angles, framed on its bbox.
Only files matching *_hand_*.obj are picked up, and outdir MUST be absolute — a relative
one makes Blender write outside the tree and silently produce nothing.
usage: blender --background --factory-startup --python render_objs.py -- objdir outdir [res] [dist]
res square render resolution in px (default 900)
dist camera distance as a multiple of the mesh radius (default 2.6; lower = tighter)"""
import bpy, sys, math, glob, os
from mathutils import Vector
argv = sys.argv[sys.argv.index("--") + 1:]
objdir, outdir = argv[0], argv[1]
RES = int(argv[2]) if len(argv) > 2 else 900
DIST = float(argv[3]) if len(argv) > 3 else 2.6
bpy.ops.wm.read_factory_settings(use_empty=True)
scn = bpy.context.scene
scn.render.engine = 'BLENDER_EEVEE' if bpy.app.version >= (4, 2) else 'BLENDER_EEVEE_NEXT'
scn.render.resolution_x = scn.render.resolution_y = RES
mat = bpy.data.materials.new("Clay")
mat.use_nodes = True
bsdf = mat.node_tree.nodes["Principled BSDF"]
bsdf.inputs["Base Color"].default_value = (0.72, 0.55, 0.45, 1.0)
bsdf.inputs["Roughness"].default_value = 0.65
for rot, energy in (((50, 0, 30), 3.0), ((-40, 0, -140), 1.2), ((10, 0, 180), 0.8)):
sun = bpy.data.objects.new("Sun", bpy.data.lights.new("Sun", 'SUN'))
sun.data.energy = energy
sun.rotation_euler = tuple(math.radians(a) for a in rot)
scn.collection.objects.link(sun)
cam = bpy.data.objects.new("Cam", bpy.data.cameras.new("Cam"))
cam.data.lens = 60
scn.collection.objects.link(cam)
scn.camera = cam
for path in sorted(glob.glob(os.path.join(objdir, "*_hand_*.obj"))):
bpy.ops.wm.obj_import(filepath=path)
obj = bpy.context.selected_objects[0]
obj.data.materials.clear()
obj.data.materials.append(mat)
for p in obj.data.polygons: p.use_smooth = True
bb = [obj.matrix_world @ Vector(c) for c in obj.bound_box]
ctr = sum(bb, Vector()) / 8
rad = max((v - ctr).length for v in bb)
tag = os.path.splitext(os.path.basename(path))[0]
# OBJ import is -Z forward +Y up by default: gltf Y-up mesh arrives Z-up in Blender
for label, direction in (("palm", Vector((0, -1, -0.25))),
("back", Vector((0, 1, 0.35))),
("side", Vector((-1, -0.3, 0.1)))):
d = direction.normalized()
cam.location = ctr - d * (rad * DIST)
cam.rotation_euler = d.to_track_quat('-Z', 'Y').to_euler()
scn.render.filepath = os.path.join(outdir, f"{tag}_{label}.png")
bpy.ops.render.render(write_still=True)
print("[objr] wrote", scn.render.filepath)
bpy.data.objects.remove(obj, do_unlink=True)
print("[objr] DONE")
+82
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"""Scan GLBs: list finger joints and which animations have live (non-frozen) finger rotation tracks."""
import json, struct, sys, math
from pathlib import Path
FINGER_TOKENS = ("thumb", "index", "middle", "ring", "pinky", "finger")
def read_glb(path):
data = Path(path).read_bytes()
magic, ver, length = struct.unpack_from("<III", data, 0)
assert magic == 0x46546C67, "not glb"
off = 12
gltf = None
bin_chunk = None
while off < length:
clen, ctype = struct.unpack_from("<II", data, off)
off += 8
chunk = data[off:off+clen]
if ctype == 0x4E4F534A:
gltf = json.loads(chunk.decode("utf-8"))
elif ctype == 0x004E4942:
bin_chunk = chunk
off += clen
return gltf, bin_chunk
def accessor_data(gltf, binc, idx):
acc = gltf["accessors"][idx]
bv = gltf["bufferViews"][acc["bufferView"]]
comp = {5126: ("f", 4)}[acc["componentType"]]
n = {"SCALAR":1, "VEC3":3, "VEC4":4}[acc["type"]]
off = bv.get("byteOffset", 0) + acc.get("byteOffset", 0)
count = acc["count"]
vals = struct.unpack_from("<%d%s" % (count*n, comp[0]), binc, off)
return [vals[i*n:(i+1)*n] for i in range(count)]
def scan(path, verbose_joints=False):
gltf, binc = read_glb(path)
nodes = gltf.get("nodes", [])
names = [nd.get("name", f"node{i}") for i, nd in enumerate(nodes)]
# joints from skins
joint_set = set()
for skin in gltf.get("skins", []):
joint_set.update(skin.get("joints", []))
fingers = sorted(n for i in joint_set for n in [names[i]] if any(t in n.lower() for t in FINGER_TOKENS))
print(f"\n== {Path(path).name} ==")
print(f"joints: {len(joint_set)}, finger joints: {len(fingers)}")
if verbose_joints:
for n in sorted(names[i] for i in joint_set):
print(" ", n)
elif fingers:
print(" finger joints:", ", ".join(fingers))
for anim in gltf.get("animations", []):
aname = anim.get("name", "?")
live, frozen = [], []
for ch in anim.get("channels", []):
tgt = ch["target"]
if tgt.get("path") != "rotation":
continue
nname = names[tgt["node"]]
if not any(t in nname.lower() for t in FINGER_TOKENS):
continue
samp = anim["samplers"][ch["sampler"]]
quats = accessor_data(gltf, binc, samp["output"])
# measure max angular deviation from first frame
q0 = quats[0]
maxdot = 1.0
for q in quats[1:]:
d = abs(sum(a*b for a, b in zip(q0, q)))
maxdot = min(maxdot, min(d, 1.0))
ang = 2*math.degrees(math.acos(maxdot))
(live if ang > 2.0 else frozen).append((nname, ang))
total = len(live) + len(frozen)
if total:
print(f" anim '{aname}': {total} finger rot tracks, {len(live)} live (>2deg), {len(frozen)} frozen")
if live:
top = sorted(live, key=lambda x: -x[1])[:4]
print(" top movers:", ", ".join(f"{n} {a:.0f}deg" for n, a in top))
else:
print(f" anim '{aname}': NO finger tracks")
if __name__ == "__main__":
for p in sys.argv[1:]:
scan(p, verbose_joints="--joints" in sys.argv)
+98
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"""Skin a baked-pose GLB's hand region with Godot-exact LBS and write it as a plain OBJ.
usage: godot_skin_hand_obj.py posed.glb side(l|r) out.obj"""
import json, struct, sys
def read_glb(path):
d = open(path, "rb").read()
length = struct.unpack_from("<I", d, 8)[0]
off = 12; g = None; b = None
while off < length:
clen, ct = struct.unpack_from("<II", d, off); off += 8
if ct == 0x4E4F534A: g = json.loads(d[off:off+clen])
else: b = d[off:off+clen]
off += clen
return g, b
def acc(g, b, i):
a = g["accessors"][i]; bv = g["bufferViews"][a["bufferView"]]
nc = {"SCALAR":1,"VEC2":2,"VEC3":3,"VEC4":4,"MAT4":16}[a["type"]]
fmt = {5121:"B",5123:"H",5125:"I",5126:"f"}[a["componentType"]]
size = struct.calcsize(fmt)*nc; stride = bv.get("byteStride") or size
off = bv.get("byteOffset",0)+a.get("byteOffset",0)
return [struct.unpack_from("<%d%s"%(nc,fmt), b, off+k*stride) for k in range(a["count"])], a["componentType"]
def quat_mat(q):
x,y,z,w = q
return [[1-2*(y*y+z*z),2*(x*y-z*w),2*(x*z+y*w)],
[2*(x*y+z*w),1-2*(x*x+z*z),2*(y*z-x*w)],
[2*(x*z-y*w),2*(y*z+x*w),1-2*(x*x+y*y)]]
def node_local(nd):
t = nd.get("translation",[0,0,0]); r = nd.get("rotation",[0,0,0,1]); s = nd.get("scale",[1,1,1])
R = quat_mat(r)
M = [[R[i][j]*s[j] for j in range(3)]+[t[i]] for i in range(3)]
return M+[[0,0,0,1]]
def matmul(A,B):
return [[sum(A[i][k]*B[k][j] for k in range(4)) for j in range(4)] for i in range(4)]
glb, side, out = sys.argv[1:4]
g, b = read_glb(glb)
names = [nd.get("name","") for nd in g["nodes"]]
loc = [node_local(nd) for nd in g["nodes"]]
parent = {}
for i,nd in enumerate(g["nodes"]):
for c in nd.get("children",[]): parent[c] = i
memo = {}
def gm(i):
if i in memo: return memo[i]
m = loc[i] if i not in parent else matmul(gm(parent[i]), loc[i])
memo[i] = m; return m
G = [gm(i) for i in range(len(g["nodes"]))]
skin = g["skins"][0]; joints = skin["joints"]
ibm,_ = acc(g,b,skin["inverseBindMatrices"])
def m16(row):
return [[row[c*4+r] for c in range(4)] for r in range(4)]
JM = [matmul(G[joints[j]], m16(ibm[j])) for j in range(len(joints))]
REGION = ("hand_", "thumb_", "index_", "middle_", "ring_", "pinky_", "lowerarm_")
region_j = {j for j in range(len(joints))
if any(names[joints[j]].startswith(p) for p in REGION)
and names[joints[j]].endswith("_"+side)}
prim = g["meshes"][0]["primitives"][0]
P,_ = acc(g,b,prim["attributes"]["POSITION"])
J,_ = acc(g,b,prim["attributes"]["JOINTS_0"])
W,wt = acc(g,b,prim["attributes"]["WEIGHTS_0"])
I,_ = acc(g,b,prim["indices"])
wsc = 1.0 if wt==5126 else (1/255 if wt==5121 else 1/65535)
keep = {}
for vi,(p,jr,wr) in enumerate(zip(P,J,W)):
if not any(j in region_j and w>0 for j,w in zip(jr,wr)): continue
x=y=z=0.0
for j,w in zip(jr,wr):
w*=wsc
if w<=0: continue
M=JM[j]
x+=w*(M[0][0]*p[0]+M[0][1]*p[1]+M[0][2]*p[2]+M[0][3])
y+=w*(M[1][0]*p[0]+M[1][1]*p[1]+M[1][2]*p[2]+M[1][3])
z+=w*(M[2][0]*p[0]+M[2][1]*p[1]+M[2][2]*p[2]+M[2][3])
keep[vi]=(x,y,z)
remap = {vi:k+1 for k,vi in enumerate(keep)}
tris = []
flat = [ix[0] for ix in I]
for t in range(0, len(flat), 3):
a1,a2,a3 = flat[t], flat[t+1], flat[t+2]
if a1 in remap and a2 in remap and a3 in remap:
tris.append((remap[a1], remap[a2], remap[a3]))
with open(out, "w") as f:
for vi in keep:
x,y,z = keep[vi]
f.write(f"v {x:.6f} {y:.6f} {z:.6f}\n")
for t in tris:
f.write(f"f {t[0]} {t[1]} {t[2]}\n")
print(f"[skinobj] {out}: {len(keep)} verts, {len(tris)} tris")
+29
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"""Trim a skin_to_obj dump to the HAND only, so a bbox-framing renderer actually frames
the hand. The dumps span the whole arm (76cm in x); the hand is the outer ~13cm.
usage: trim_hand.py <in.obj> <out.obj> <l|r>"""
import sys
src, dst, side = sys.argv[1], sys.argv[2], sys.argv[3]
verts, faces = [], []
for line in open(src):
if line.startswith("v "):
verts.append([float(x) for x in line.split()[1:4]])
elif line.startswith("f "):
faces.append([int(t.split("/")[0]) - 1 for t in line.split()[1:]])
xs = [v[0] for v in verts]
# hand sits at the far end in |x|; keep the outer 15cm of the limb
cut = (max(xs) - 0.15) if side == "l" else (min(xs) + 0.15)
keep = [(v[0] >= cut) if side == "l" else (v[0] <= cut) for v in verts]
remap, out_v = {}, []
for i, v in enumerate(verts):
if keep[i]:
remap[i] = len(out_v)
out_v.append(v)
out_f = [f for f in faces if all(i in remap for i in f)]
with open(dst, "w") as f:
for v in out_v:
f.write(f"v {v[0]:.6f} {v[1]:.6f} {v[2]:.6f}\n")
for fc in out_f:
f.write("f " + " ".join(str(remap[i] + 1) for i in fc) + "\n")
print(f"[trim] {dst}: {len(out_v)}/{len(verts)} verts, {len(out_f)} faces (cut x={cut:.3f})")
+41
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"""Regenerate hand-poses/canonical_rest.json — the canonical Quaternius finger-bone REST
rotations, taken from the Kevin pack the hand poses were harvested against.
The runtime needs this to apply a pose REST-RELATIVE on rigs whose finger rest differs from
canonical (Mako's *_01 knuckles sit 11.5 deg off, so applying a canonical pose directly
rotates his knuckles away from his own rest and tears the palm/wrist boundary):
delta = canonical_rest^-1 * pose
target = body_rest * delta
usage: make_canonical_rest.py [kevin.glb] [out.json]
"""
import json, struct, sys
from pathlib import Path
REPO = Path(__file__).resolve().parents[1]
GAME = REPO.parent / "ariki-game"
src = Path(sys.argv[1]) if len(sys.argv) > 1 else \
GAME / "assets/quaternius/kevin/kevin_female_combat.glb"
out = Path(sys.argv[2]) if len(sys.argv) > 2 else REPO / "hand-poses/canonical_rest.json"
d = src.read_bytes()
jl = struct.unpack_from("<I", d, 12)[0]
g = json.loads(d[20:20 + jl].decode("utf-8"))
pose_bones = list(json.loads((REPO / "hand-poses/pose_flat.json").read_text())["bones"])
rest = {nd.get("name"): nd.get("rotation", [0, 0, 0, 1]) for nd in g["nodes"]}
missing = [b for b in pose_bones if b not in rest]
if missing:
raise SystemExit(f"canonical source lacks pose bones: {missing}")
payload = {
"_comment": ("Canonical Quaternius finger-bone REST rotations. The runtime applies a "
"pose rest-relative: delta = canonical_rest^-1 * pose, "
"target = body_rest * delta. Regenerate with tools/make_canonical_rest.py."),
"source": src.name,
"bones": {b: [round(v, 8) for v in rest[b]] for b in pose_bones},
}
out.write_text(json.dumps(payload, indent=1))
print(f"wrote {out} with {len(payload['bones'])} bones from {src.name}")
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"""Crop an OBJ to the faces fully inside a sphere, so clay renders can frame the hand
instead of the whole arm. Keeps vertex order stable across files (same face set in/out)
only when the inputs share topology, so pass --like to reuse a reference file's face mask.
usage: obj_crop.py in.obj out.obj CX CY CZ R (metres)
obj_crop.py in.obj out.obj --mask mask.txt
obj_crop.py in.obj --write-mask mask.txt CX CY CZ R
"""
import sys, math
from pathlib import Path
def load(path):
vs, faces = [], []
for line in Path(path).read_text().splitlines():
if line.startswith("v "):
p = line.split()
vs.append((float(p[1]), float(p[2]), float(p[3])))
elif line.startswith("f "):
faces.append([int(t.split("/")[0]) - 1 for t in line.split()[1:]])
return vs, faces
args = sys.argv[1:]
src = args[0]
vs, faces = load(src)
if "--write-mask" in args:
maskfile = args[args.index("--write-mask") + 1]
cx, cy, cz, r = (float(x) for x in args[-4:])
keep = [i for i, f in enumerate(faces)
if all(math.dist(vs[k], (cx, cy, cz)) <= r for k in f)]
Path(maskfile).write_text("\n".join(map(str, keep)))
print(f"mask {len(keep)}/{len(faces)} faces -> {maskfile}")
sys.exit()
dst = args[1]
if "--mask" in args:
keep = [int(x) for x in Path(args[args.index("--mask") + 1]).read_text().split()]
else:
cx, cy, cz, r = (float(x) for x in args[-4:])
keep = [i for i, f in enumerate(faces)
if all(math.dist(vs[k], (cx, cy, cz)) <= r for k in f)]
used = sorted({k for i in keep for k in faces[i]})
remap = {old: n + 1 for n, old in enumerate(used)}
out = [f"v {vs[o][0]:.6f} {vs[o][1]:.6f} {vs[o][2]:.6f}" for o in used]
out += ["f " + " ".join(str(remap[k]) for k in faces[i]) for i in keep]
Path(dst).write_text("\n".join(out) + "\n")
print(f"{Path(dst).name}: {len(used)} verts, {len(keep)} faces")
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"""Count connected components in a slab of an OBJ, to tell separated digits from a fused
mitt. Slice just past the knuckles: 4 components = separate fingers, 1 = fused paddle.
usage: obj_slice_components.py mesh.obj AXIS LO HI (axis x|y|z, bounds in metres)
"""
import sys
from pathlib import Path
from collections import defaultdict, deque
path, axis, lo, hi = sys.argv[1], sys.argv[2], float(sys.argv[3]), float(sys.argv[4])
ai = {"x": 0, "y": 1, "z": 2}[axis]
vs, faces = [], []
for line in Path(path).read_text().splitlines():
if line.startswith("v "):
p = line.split()
vs.append((float(p[1]), float(p[2]), float(p[3])))
elif line.startswith("f "):
faces.append([int(t.split("/")[0]) - 1 for t in line.split()[1:]])
inslab = [i for i, v in enumerate(vs) if lo <= v[ai] <= hi]
sel = set(inslab)
adj = defaultdict(set)
kept = 0
for f in faces:
if all(k in sel for k in f):
kept += 1
for a in f:
for b in f:
if a != b:
adj[a].add(b)
seen = set()
comps = []
for v in inslab:
if v in seen:
continue
q = deque([v]); seen.add(v); c = []
while q:
u = q.popleft(); c.append(u)
for w in adj.get(u, ()):
if w not in seen:
seen.add(w); q.append(w)
comps.append(c)
comps.sort(key=len, reverse=True)
print(f"{Path(path).name} slab {axis} in [{lo}, {hi}]")
print(f" verts in slab {len(inslab)}, faces kept {kept}, components {len(comps)}")
for n, c in enumerate(comps[:10]):
if len(c) < 4:
continue
ext = [(min(vs[k][d] for k in c) * 100, max(vs[k][d] for k in c) * 100) for d in range(3)]
span = [f"{e[1]-e[0]:.1f}" for e in ext]
ctr = [f"{(e[0]+e[1])/2:.1f}" for e in ext]
print(f" comp{n}: {len(c):5d} verts span(cm) x{span[0]} y{span[1]} z{span[2]}"
f" centre({ctr[0]}, {ctr[1]}, {ctr[2]})")
big = [c for c in comps if len(c) >= 20]
print(f" components with >=20 verts: {len(big)}")
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"""Compare finger-bone REST rotations between GLB skeletons.
First GLB is the reference; each other is reported as per-bone angle deviation (degrees).
usage: rest_deviation.py canonical.glb other.glb [more.glb ...]
"""
import json, struct, sys, math
from pathlib import Path
FING = ("thumb", "index", "middle", "ring", "pinky")
def read_gltf(path):
d = Path(path).read_bytes()
jlen = struct.unpack_from("<I", d, 12)[0]
return json.loads(d[20:20 + jlen].decode("utf-8"))
def rests(path):
g = read_gltf(path)
out = {}
for nd in g["nodes"]:
n = nd.get("name", "")
if any(t in n.lower() for t in FING):
out[n] = nd.get("rotation", [0, 0, 0, 1])
return out
def angle_between(a, b):
"""Geodesic angle (deg) between two unit quaternions, sign-insensitive."""
d = abs(sum(x * y for x, y in zip(a, b)))
d = max(-1.0, min(1.0, d))
return math.degrees(2 * math.acos(d))
ref_path = sys.argv[1]
ref = rests(ref_path)
print(f"reference: {Path(ref_path).name} ({len(ref)} finger bones)")
for p in sys.argv[2:]:
other = rests(p)
print(f"\n== {Path(p).name} == {len(other)} finger bones")
missing = sorted(set(ref) - set(other))
extra = sorted(set(other) - set(ref))
if missing:
print(f" MISSING vs ref ({len(missing)}): {', '.join(missing)}")
if extra:
print(f" EXTRA vs ref ({len(extra)}): {', '.join(extra)}")
devs = []
for n in sorted(set(ref) & set(other)):
devs.append((angle_between(ref[n], other[n]), n))
devs.sort(reverse=True)
if not devs:
continue
over = [d for d in devs if d[0] > 1.0]
print(f" shared {len(devs)} | deviating >1deg: {len(over)} | max {devs[0][0]:.1f}deg ({devs[0][1]})")
for d, n in devs[:12]:
print(f" {n:24s} {d:6.1f}deg")
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"""Per-finger-bone territory audit: how many verts does each finger bone actually OWN
(dominant weight) and how much total weight mass does it carry?
Why: fin_bones classifies exp05's fist tears as hand<->thumb_02 and hand<->index_02 —
the chain skips the _01 joints. If the _01 bones own no territory, every curl lands as a
hard one-edge step from the palm to phalanx 2, which must stretch. This measures that
directly instead of inferring it. usage: bone_territory.py body.glb
"""
import json
import struct
import sys
from pathlib import Path
DIGITS = ("thumb", "index", "middle", "ring", "pinky")
def read_glb(path):
d = Path(path).read_bytes()
ln = struct.unpack_from("<I", d, 8)[0]
off, g, b = 12, None, None
while off < ln:
clen, ct = struct.unpack_from("<II", d, off)
off += 8
if ct == 0x4E4F534A:
g = json.loads(d[off:off + clen])
else:
b = d[off:off + clen]
off += clen
return g, b
def acc(g, b, i):
a = g["accessors"][i]
bv = g["bufferViews"][a["bufferView"]]
nc = {"SCALAR": 1, "VEC2": 2, "VEC3": 3, "VEC4": 4, "MAT4": 16}[a["type"]]
fmt = {5121: "B", 5123: "H", 5125: "I", 5126: "f"}[a["componentType"]]
sz = struct.calcsize(fmt) * nc
stride = bv.get("byteStride") or sz
off = bv.get("byteOffset", 0) + a.get("byteOffset", 0)
out = []
for k in range(a["count"]):
out.append(struct.unpack_from("<" + fmt * nc, b, off + k * stride))
return out
g, b = read_glb(sys.argv[1])
prim = g["meshes"][0]["primitives"][0]
joints = g["skins"][0]["joints"]
names = [g["nodes"][j].get("name", f"node{j}") for j in joints]
J = acc(g, b, prim["attributes"]["JOINTS_0"])
W = acc(g, b, prim["attributes"]["WEIGHTS_0"])
wt = g["accessors"][prim["attributes"]["WEIGHTS_0"]]["componentType"]
sc = 1.0 if wt == 5126 else (1 / 255 if wt == 5121 else 1 / 65535)
own = {n: 0 for n in names} # verts whose LARGEST weight is this bone
mass = {n: 0.0 for n in names} # total weight mass
any_w = {n: 0 for n in names} # verts with any weight >1%
for ji, wi in zip(J, W):
ws = [w * sc for w in wi]
best, bw = None, 0.0
for jj, w in zip(ji, ws):
n = names[jj]
mass[n] += w
if w > 0.01:
any_w[n] += 1
if w > bw:
best, bw = n, w
if best is not None and bw > 0:
own[best] += 1
print(f"{Path(sys.argv[1]).name} {len(J)} verts, {len(joints)} joints")
print(f"{'bone':16s} {'owns':>7s} {'any>1%':>8s} {'mass':>9s}")
for side in ("l", "r"):
print(f"--- hand_{side} chain ---")
for nm in [f"hand_{side}"] + [f"{d}_{p}_{side}" for d in DIGITS
for p in ("01", "02", "03")]:
if nm not in own:
print(f"{nm:16s} (absent from skin)")
continue
flag = " <-- STARVED" if own[nm] == 0 else ""
print(f"{nm:16s} {own[nm]:7d} {any_w[nm]:8d} {mass[nm]:9.1f}{flag}")
+272
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"""Repair cross-midline finger skin bindings by INPAINTING from the mesh's own healthy
neighbours.
Mako's shipped rig binds ~444 left-hand verts to RIGHT middle-finger bones (many at weight
1.0, lever arm ~1.8 m), so any middle-finger rotation hurls them across the body. A blunt
_r -> _l mirror remap does NOT fix it: those verts sit 5.8-10.5 cm from the mirrored bone and
their nearest correct joints are thumb/pinky, so remapping would bind thumb skin to the middle
finger and tear. Instead we discard the corrupt influences and refill each vert from its
HEALTHY neighbours on the same mesh (topological BFS first, spatial fallback), which is exactly
what the surrounding 13k correctly-bound left-hand verts already encode.
usage:
skin_crosshand_repair.py in.glb out.glb [--diagnose] [--k 8] [--report]
--diagnose analyse and print only, write nothing
--k N neighbours to blend per repaired vert (default 8)
"""
import json, struct, sys, math
from pathlib import Path
from collections import deque, defaultdict
FING = ("thumb", "index", "middle", "ring", "pinky")
MID = 0.02 # metres either side of x=0 that counts as "across the midline"
def read_glb(p):
d = Path(p).read_bytes()
length = struct.unpack_from("<I", d, 8)[0]
off = 12
chunks = []
g = None
while off < length:
clen, ct = struct.unpack_from("<II", d, off)
off += 8
if ct == 0x4E4F534A:
g = json.loads(d[off:off + clen].decode("utf-8"))
chunks.append([ct, None])
else:
chunks.append([ct, bytearray(d[off:off + clen])])
off += clen
return g, chunks
def write_glb(path, g, chunks):
js = json.dumps(g, separators=(",", ":")).encode("utf-8")
js += b" " * ((4 - len(js) % 4) % 4)
body = b""
for ct, payload in chunks:
if ct == 0x4E4F534A:
payload = js
body += struct.pack("<II", len(payload), ct) + bytes(payload)
Path(path).write_bytes(struct.pack("<III", 0x46546C67, 2, 12 + len(body)) + body)
def acc_info(g, i):
a = g["accessors"][i]
bv = g["bufferViews"][a["bufferView"]]
nc = {"SCALAR": 1, "VEC2": 2, "VEC3": 3, "VEC4": 4, "MAT4": 16}[a["type"]]
fmt = {5121: "B", 5123: "H", 5125: "I", 5126: "f"}[a["componentType"]]
size = struct.calcsize(fmt) * nc
stride = bv.get("byteStride") or size
off = bv.get("byteOffset", 0) + a.get("byteOffset", 0)
return a, bv, nc, fmt, stride, off
def read_acc(g, buf, i):
a, bv, nc, fmt, stride, off = acc_info(g, i)
return [struct.unpack_from("<%d%s" % (nc, fmt), buf, off + k * stride)
for k in range(a["count"])]
def quat_mat(q):
x, y, z, w = q
return [[1 - 2 * (y * y + z * z), 2 * (x * y - z * w), 2 * (x * z + y * w)],
[2 * (x * y + z * w), 1 - 2 * (x * x + z * z), 2 * (y * z - x * w)],
[2 * (x * z - y * w), 2 * (y * z + x * w), 1 - 2 * (x * x + y * y)]]
def node_local(nd):
t = nd.get("translation", [0, 0, 0])
r = nd.get("rotation", [0, 0, 0, 1])
s = nd.get("scale", [1, 1, 1])
R = quat_mat(r)
return [[R[i][j] * s[j] for j in range(3)] + [t[i]] for i in range(3)] + [[0, 0, 0, 1]]
def matmul(A, B):
return [[sum(A[i][k] * B[k][j] for k in range(4)) for j in range(4)] for i in range(4)]
def global_mats(g):
loc = [node_local(nd) for nd in g["nodes"]]
parent = {}
for i, nd in enumerate(g["nodes"]):
for c in nd.get("children", []):
parent[c] = i
memo = {}
def gm(i):
if i in memo:
return memo[i]
m = loc[i]
p = parent.get(i)
if p is not None:
m = matmul(gm(p), m)
memo[i] = m
return m
return [gm(i) for i in range(len(g["nodes"]))]
# ---------------------------------------------------------------- main
argv = sys.argv[1:]
src = argv[0]
dst = argv[1] if len(argv) > 1 and not argv[1].startswith("--") else None
DIAG = "--diagnose" in argv
K = int(argv[argv.index("--k") + 1]) if "--k" in argv else 8
g, chunks = read_glb(src)
buf = next(p for ct, p in chunks if ct == 0x004E4942)
names = [nd.get("name", "") for nd in g["nodes"]]
GM = global_mats(g)
total_fixed = 0
for mi, mesh in enumerate(g.get("meshes", [])):
for pi, prim in enumerate(mesh.get("primitives", [])):
att = prim["attributes"]
if "JOINTS_0" not in att:
continue
skin_idx = next((nd.get("skin") for nd in g["nodes"]
if nd.get("mesh") == mi and "skin" in nd), None)
if skin_idx is None:
continue
joints = g["skins"][skin_idx]["joints"]
jname = [names[j] for j in joints]
jpos = [(GM[j][0][3], GM[j][1][3], GM[j][2][3]) for j in joints]
P = read_acc(g, buf, att["POSITION"])
J = [list(r) for r in read_acc(g, buf, att["JOINTS_0"])]
Wr = read_acc(g, buf, att["WEIGHTS_0"])
_, _, _, wfmt, _, _ = acc_info(g, att["WEIGHTS_0"])
wsc = 1.0 if wfmt == "f" else (1 / 255 if wfmt == "B" else 1 / 65535)
W = [[w * wsc for w in r] for r in Wr]
is_fing = [any(t in n.lower() for t in FING) for n in jname]
side = ["l" if n.lower().endswith("_l") else ("r" if n.lower().endswith("_r") else "")
for n in jname]
# ---- classify corrupt refs
corrupt = defaultdict(list) # vert -> [slot,...]
for vi, (p, jrow, wrow) in enumerate(zip(P, J, W)):
for s, (j, w) in enumerate(zip(jrow, wrow)):
if w <= 0.001 or not is_fing[j]:
continue
if (side[j] == "r" and p[0] > MID) or (side[j] == "l" and p[0] < -MID):
corrupt[vi].append(s)
if not corrupt:
print(f" mesh[{mi}] prim{pi}: no cross-midline finger refs — nothing to do")
continue
bad_verts = set(corrupt)
nref = sum(len(v) for v in corrupt.values())
print(f" mesh[{mi}] '{mesh.get('name','')}' prim{pi}: {len(P)} verts")
print(f" corrupt refs {nref} across {len(bad_verts)} verts")
# ---- topology adjacency
adj = defaultdict(set)
if "indices" in prim:
idx = [r[0] for r in read_acc(g, buf, prim["indices"])]
for t in range(0, len(idx) - 2, 3):
a_, b_, c_ = idx[t], idx[t + 1], idx[t + 2]
adj[a_].update((b_, c_))
adj[b_].update((a_, c_))
adj[c_].update((a_, b_))
# healthy = not corrupt AND has some weight
def healthy(v):
return v not in bad_verts and sum(W[v]) > 0.5
# spatial fallback pool: healthy verts near the affected region
cx = sum(P[v][0] for v in bad_verts) / len(bad_verts)
cy = sum(P[v][1] for v in bad_verts) / len(bad_verts)
cz = sum(P[v][2] for v in bad_verts) / len(bad_verts)
pool = [v for v in range(len(P))
if healthy(v) and abs(P[v][0] - cx) < 0.30
and abs(P[v][1] - cy) < 0.30 and abs(P[v][2] - cz) < 0.30]
print(f" healthy donor pool near region: {len(pool)} verts")
topo_used = spatial_used = 0
newJ, newW = {}, {}
for vi in sorted(bad_verts):
# BFS out to healthy neighbours through the mesh
found = []
seen = {vi}
q = deque([(vi, 0)])
while q and len(found) < K:
v, d = q.popleft()
if d > 4:
continue
for nb in adj.get(v, ()):
if nb in seen:
continue
seen.add(nb)
if healthy(nb):
found.append(nb)
if len(found) >= K:
break
q.append((nb, d + 1))
if found:
topo_used += 1
else:
# spatial fallback
ds = sorted(((math.dist(P[vi], P[v]), v) for v in pool))[:K]
found = [v for _, v in ds]
spatial_used += 1
# inverse-distance blend of neighbour weight sets
accw = defaultdict(float)
for nb in found:
d = math.dist(P[vi], P[nb])
wgt = 1.0 / max(d, 1e-4)
for j, w in zip(J[nb], W[nb]):
if w > 0.001:
accw[j] += w * wgt
# keep top 4, renormalise
top = sorted(accw.items(), key=lambda kv: -kv[1])[:4]
tot = sum(w for _, w in top)
if tot <= 0:
continue
nj = [0, 0, 0, 0]
nw = [0.0, 0.0, 0.0, 0.0]
for s, (j, w) in enumerate(top):
nj[s] = j
nw[s] = w / tot
newJ[vi] = nj
newW[vi] = nw
print(f" repaired {len(newJ)} verts (topological {topo_used}, spatial fallback {spatial_used})")
total_fixed += len(newJ)
if DIAG:
# show what the repair decided for a few verts
for vi in sorted(newJ)[:6]:
before = " ".join(f"{jname[j]}={w:.3f}" for j, w in zip(J[vi], W[vi]) if w > 0.001)
after = " ".join(f"{jname[j]}={w:.3f}" for j, w in zip(newJ[vi], newW[vi]) if w > 0.001)
print(f" v{vi}\n before: {before}\n after : {after}")
continue
# ---- write back
aJ, bvJ, ncJ, fmtJ, strideJ, offJ = acc_info(g, att["JOINTS_0"])
aW, bvW, ncW, fmtW, strideW, offW = acc_info(g, att["WEIGHTS_0"])
for vi in newJ:
struct.pack_into("<4%s" % fmtJ, buf, offJ + vi * strideJ, *newJ[vi])
if fmtW == "f":
vals = newW[vi]
elif fmtW == "B":
vals = [max(0, min(255, int(round(w * 255)))) for w in newW[vi]]
vals[0] += 255 - sum(vals)
else:
vals = [max(0, min(65535, int(round(w * 65535)))) for w in newW[vi]]
vals[0] += 65535 - sum(vals)
struct.pack_into("<4%s" % fmtW, buf, offW + vi * strideW, *vals)
if DIAG:
print("\ndiagnose only — nothing written")
elif dst:
write_glb(dst, g, chunks)
print(f"\nwrote {dst} ({total_fixed} verts repaired)")
else:
print("\nno output path given — nothing written")
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"""Pure-python linear-blend skinning check: skin a GLB's verts with its current node TRS
(what Godot would render) and report max displacement of finger-weighted verts vs the
original file. usage: skin_check.py posed.glb original.glb"""
import json, struct, sys, math
from pathlib import Path
FING = ("thumb", "index", "middle", "ring", "pinky")
def read_glb(path):
d = Path(path).read_bytes()
length = struct.unpack_from("<I", d, 8)[0]
off = 12; g = None; b = None
while off < length:
clen, ct = struct.unpack_from("<II", d, off); off += 8
if ct == 0x4E4F534A: g = json.loads(d[off:off+clen])
else: b = d[off:off+clen]
off += clen
return g, b
def acc(g, b, i):
a = g["accessors"][i]; bv = g["bufferViews"][a["bufferView"]]
nc = {"SCALAR":1,"VEC2":2,"VEC3":3,"VEC4":4,"MAT4":16}[a["type"]]
fmt = {5121:"B",5123:"H",5125:"I",5126:"f"}[a["componentType"]]
size = struct.calcsize(fmt)*nc; stride = bv.get("byteStride") or size
off = bv.get("byteOffset",0)+a.get("byteOffset",0)
return [struct.unpack_from("<%d%s"%(nc,fmt), b, off+i*stride) for i in range(a["count"])], a["componentType"]
def quat_mat(q):
x,y,z,w = q
return [[1-2*(y*y+z*z),2*(x*y-z*w),2*(x*z+y*w)],
[2*(x*y+z*w),1-2*(x*x+z*z),2*(y*z-x*w)],
[2*(x*z-y*w),2*(y*z+x*w),1-2*(x*x+y*y)]]
def node_local(nd):
t = nd.get("translation",[0,0,0]); r = nd.get("rotation",[0,0,0,1]); s = nd.get("scale",[1,1,1])
R = quat_mat(r)
M = [[R[i][j]*s[j] for j in range(3)]+[t[i]] for i in range(3)]
return M+[[0,0,0,1]]
def matmul(A,B):
return [[sum(A[i][k]*B[k][j] for k in range(4)) for j in range(4)] for i in range(4)]
def globals_(g):
loc = [node_local(nd) for nd in g["nodes"]]
parent = {}
for i,nd in enumerate(g["nodes"]):
for c in nd.get("children",[]): parent[c] = i
memo = {}
def gm(i):
if i in memo: return memo[i]
m = loc[i] if i not in parent else matmul(gm(parent[i]), loc[i])
memo[i] = m; return m
return [gm(i) for i in range(len(g["nodes"]))]
def skinned_positions(g, b, only_finger=True):
names = [nd.get("name","") for nd in g["nodes"]]
G = globals_(g)
skin = g["skins"][0]
joints = skin["joints"]
ibm, _ = acc(g, b, skin["inverseBindMatrices"])
# glTF matrices are column-major
def m16(row):
return [[row[c*4+r] for c in range(4)] for r in range(4)]
JM = [matmul(G[joints[j]], m16(ibm[j])) for j in range(len(joints))]
prim = g["meshes"][0]["primitives"][0]
P,_ = acc(g,b,prim["attributes"]["POSITION"])
J,_ = acc(g,b,prim["attributes"]["JOINTS_0"])
W,wt = acc(g,b,prim["attributes"]["WEIGHTS_0"])
wsc = 1.0 if wt==5126 else (1/255 if wt==5121 else 1/65535)
out = {}
for vi,(p,jr,wr) in enumerate(zip(P,J,W)):
if only_finger and not any(any(t in names[joints[j]].lower() for t in FING)
for j,w in zip(jr,wr) if w>0):
continue
x=y=z=0.0
for j,w in zip(jr,wr):
w*=wsc
if w<=0: continue
M=JM[j]
x+=w*(M[0][0]*p[0]+M[0][1]*p[1]+M[0][2]*p[2]+M[0][3])
y+=w*(M[1][0]*p[0]+M[1][1]*p[1]+M[1][2]*p[2]+M[1][3])
z+=w*(M[2][0]*p[0]+M[2][1]*p[1]+M[2][2]*p[2]+M[2][3])
out[vi]=(x,y,z)
return out, names, joints
posed_g, posed_b = read_glb(sys.argv[1])
orig_g, orig_b = read_glb(sys.argv[2])
a, names, joints = skinned_positions(posed_g, posed_b)
c, _, _ = skinned_positions(orig_g, orig_b)
dmax = 0; worst = None
for vi in a:
d = math.dist(a[vi], c[vi])
if d > dmax: dmax, worst = d, vi
print(f"finger-weighted verts: {len(a)}; max displacement posed-vs-original: {dmax*100:.1f} cm (vert {worst})")
import statistics
ds = sorted(math.dist(a[vi], c[vi]) for vi in a)
print(f"median: {ds[len(ds)//2]*100:.2f} cm, p95: {ds[int(len(ds)*0.95)]*100:.2f} cm")
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"""Find corrupt skin bindings: verts bound to a joint that is implausibly far away in
REST pose (long bind lever arm), and verts bound across the body midline to the opposite
hand's bones. These are invisible at rest and only explode once the joint rotates.
usage: skin_lever_audit.py body.glb [--lever CM] [--dump N]
"""
import json, struct, sys, math
from pathlib import Path
from collections import Counter, defaultdict
FING = ("thumb", "index", "middle", "ring", "pinky")
LEVER_CM = 20.0
DUMP = 0
args = [a for a in sys.argv[1:]]
path = args[0]
if "--lever" in args:
LEVER_CM = float(args[args.index("--lever") + 1])
if "--dump" in args:
DUMP = int(args[args.index("--dump") + 1])
def read_glb(p):
d = Path(p).read_bytes()
length = struct.unpack_from("<I", d, 8)[0]
off = 12
g = b_ = None
while off < length:
clen, ct = struct.unpack_from("<II", d, off)
off += 8
if ct == 0x4E4F534A:
g = json.loads(d[off:off + clen])
else:
b_ = d[off:off + clen]
off += clen
return g, b_
def acc(g, b, i):
a = g["accessors"][i]
bv = g["bufferViews"][a["bufferView"]]
nc = {"SCALAR": 1, "VEC2": 2, "VEC3": 3, "VEC4": 4, "MAT4": 16}[a["type"]]
fmt = {5121: "B", 5123: "H", 5125: "I", 5126: "f"}[a["componentType"]]
size = struct.calcsize(fmt) * nc
stride = bv.get("byteStride") or size
off = bv.get("byteOffset", 0) + a.get("byteOffset", 0)
return [struct.unpack_from("<%d%s" % (nc, fmt), b, off + k * stride)
for k in range(a["count"])], a["componentType"]
def quat_mat(q):
x, y, z, w = q
return [[1 - 2 * (y * y + z * z), 2 * (x * y - z * w), 2 * (x * z + y * w)],
[2 * (x * y + z * w), 1 - 2 * (x * x + z * z), 2 * (y * z - x * w)],
[2 * (x * z - y * w), 2 * (y * z + x * w), 1 - 2 * (x * x + y * y)]]
def node_local(nd):
t = nd.get("translation", [0, 0, 0])
r = nd.get("rotation", [0, 0, 0, 1])
s = nd.get("scale", [1, 1, 1])
R = quat_mat(r)
return [[R[i][j] * s[j] for j in range(3)] + [t[i]] for i in range(3)] + [[0, 0, 0, 1]]
def matmul(A, B):
return [[sum(A[i][k] * B[k][j] for k in range(4)) for j in range(4)] for i in range(4)]
def global_mats(g):
loc = [node_local(nd) for nd in g["nodes"]]
parent = {}
for i, nd in enumerate(g["nodes"]):
for c in nd.get("children", []):
parent[c] = i
memo = {}
def gm(i):
if i in memo:
return memo[i]
m = loc[i]
p = parent.get(i)
if p is not None:
m = matmul(gm(p), m)
memo[i] = m
return m
return [gm(i) for i in range(len(g["nodes"]))]
g, b = read_glb(path)
names = [nd.get("name", "") for nd in g["nodes"]]
GM = global_mats(g)
print(f"== {Path(path).name} ==")
print(f" lever threshold {LEVER_CM:.0f} cm\n")
for mi, mesh in enumerate(g.get("meshes", [])):
for pi, prim in enumerate(mesh.get("primitives", [])):
att = prim["attributes"]
if "JOINTS_0" not in att:
continue
skin_idx = next((nd.get("skin") for nd in g["nodes"]
if nd.get("mesh") == mi and "skin" in nd), None)
if skin_idx is None:
continue
joints = g["skins"][skin_idx]["joints"]
jname = [names[j] for j in joints]
# joint rest world positions
jpos = [(GM[j][0][3], GM[j][1][3], GM[j][2][3]) for j in joints]
P, _ = acc(g, b, att["POSITION"])
J, _ = acc(g, b, att["JOINTS_0"])
W, wt = acc(g, b, att["WEIGHTS_0"])
wsc = 1.0 if wt == 5126 else (1 / 255 if wt == 5121 else 1 / 65535)
long_lever = []
cross = []
by_joint = Counter()
cross_by_joint = Counter()
for vi, (p, jrow, wrow) in enumerate(zip(P, J, W)):
for j, w in zip(jrow, wrow):
w *= wsc
if w <= 0.001:
continue
n = jname[j]
nl = n.lower()
if not any(t in nl for t in FING):
continue
jp = jpos[j]
d = math.dist(p, jp) * 100.0 # cm (glTF metres)
if d > LEVER_CM:
long_lever.append((d, vi, n, w, p))
by_joint[n] += 1
# cross-hand: vert on opposite side of midline from the joint
if nl.endswith("_r") and p[0] > 0.02:
cross.append((d, vi, n, w, p)); cross_by_joint[n] += 1
elif nl.endswith("_l") and p[0] < -0.02:
cross.append((d, vi, n, w, p)); cross_by_joint[n] += 1
print(f" mesh[{mi}] '{mesh.get('name','')}' prim{pi}: {len(P)} verts")
print(f" finger refs with lever > {LEVER_CM:.0f} cm : {len(long_lever)}")
if long_lever:
mx = max(long_lever)
print(f" worst {mx[0]:.1f} cm vert {mx[1]} joint {mx[2]} w={mx[3]:.3f}")
for n, c in by_joint.most_common(10):
print(f" {n:22s} {c}")
print(f" cross-midline finger refs : {len(cross)}")
if cross:
mx = max(cross)
print(f" worst {mx[0]:.1f} cm vert {mx[1]} joint {mx[2]} w={mx[3]:.3f}")
for n, c in cross_by_joint.most_common(10):
print(f" {n:22s} {c}")
for d, vi, n, w, p in sorted(long_lever, reverse=True)[:DUMP]:
print(f" v{vi} {n} w={w:.3f} lever={d:.1f}cm pos=({p[0]*100:.1f},{p[1]*100:.1f},{p[2]*100:.1f})cm")
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"""Sum skin weights per bone group (finger vs hand vs rest) for each GLB. usage: weight_audit.py *.glb"""
import json, struct, sys
from pathlib import Path
FING = ("thumb", "index", "middle", "ring", "pinky")
def read_glb(path):
data = Path(path).read_bytes()
length = struct.unpack_from("<I", data, 8)[0]
off = 12; gltf = None; binc = None
while off < length:
clen, ctype = struct.unpack_from("<II", data, off); off += 8
if ctype == 0x4E4F534A: gltf = json.loads(data[off:off+clen])
elif ctype == 0x004E4942: binc = data[off:off+clen]
off += clen
return gltf, binc
def acc(gltf, binc, idx):
a = gltf["accessors"][idx]
bv = gltf["bufferViews"][a["bufferView"]]
ncomp = {"SCALAR":1, "VEC2":2, "VEC3":3, "VEC4":4}[a["type"]]
fmt = {5121:"B", 5123:"H", 5125:"I", 5126:"f"}[a["componentType"]]
stride = bv.get("byteStride")
size = struct.calcsize(fmt)*ncomp
off = bv.get("byteOffset",0) + a.get("byteOffset",0)
out = []
for i in range(a["count"]):
o = off + i*(stride or size)
out.append(struct.unpack_from("<%d%s" % (ncomp, fmt), binc, o))
return out, a["componentType"]
for path in sys.argv[1:]:
gltf, binc = read_glb(path)
names = [nd.get("name", "") for nd in gltf["nodes"]]
print(f"\n== {Path(path).name} ==")
for mi, mesh in enumerate(gltf.get("meshes", [])):
for pi, prim in enumerate(mesh.get("primitives", [])):
att = prim["attributes"]
if "JOINTS_0" not in att: continue
# which skin uses this mesh
skin_idx = next((nd.get("skin") for nd in gltf["nodes"]
if nd.get("mesh") == mi and "skin" in nd), None)
if skin_idx is None: continue
joints = gltf["skins"][skin_idx]["joints"]
jn = [names[j] for j in joints]
J, _ = acc(gltf, binc, att["JOINTS_0"])
W, wt = acc(gltf, binc, att["WEIGHTS_0"])
wsc = 1.0 if wt == 5126 else (1/255 if wt == 5121 else 1/65535)
fing_w = hand_w = 0.0
fing_verts = 0
for jrow, wrow in zip(J, W):
fv = 0
for j, w in zip(jrow, wrow):
w *= wsc
if w <= 0: continue
n = jn[j].lower()
if any(t in n for t in FING): fing_w += w; fv = 1
elif n.startswith("hand"): hand_w += w
fing_verts += fv
print(f" mesh[{mi}] '{mesh.get('name','')}' prim{pi}: {len(J)} verts | "
f"finger-weighted verts: {fing_verts} | total finger W: {fing_w:.0f} | hand W: {hand_w:.0f}")