feat: clothing lane, character sources, and DCC bridges
Bulk import of the working lanes that were living untracked on the PC. Content: - characters/ Lena/male body lanes, bakes, texture work, run logs - clothing/ garment pipeline, configs, gates, contract docs - garments/ MD-authored garment sources (.zprj/.zpac) - UAL-Lib/ Universal Animation Library 2 source (.blend/.fbx/.glb) - tools/ blender_bridge, iclone_bridge, md_bridge, tailor, glm_agent - docs/, plans/, dev/, .agents/plans/ Repo hygiene: - .gitattributes: LFS now covers .blend, .zprj, .zpac, .obj, .npy and the Reallusion .iAvatar/.ccAvatar/.ccRestore containers. Without this the ~3.8 GB in this commit would land as raw blobs. .png/.jpg are left out on purpose — ~250 are already tracked raw and converting them would rewrite every one without shrinking history. - .gitignore: exclude /accurig/ (~1 GB AccuRig program files, redistributable from Reallusion, nothing authored here) and /dev/null/ (git-lfs hook copies dropped by a `>/dev/null` redirect on Windows). Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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# Stage 32 (read-only): why did 4,502 triangles (3.66% of her surface) fail to rasterise into the
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# new atlas? They render as grey tears, so they are not the harmless sub-texel slivers I assumed.
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#
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# blender --background --python 32_skipprobe.py -- <seamed.blend>
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import bpy, sys
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import numpy as np
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BLEND = sys.argv[sys.argv.index("--") + 1]
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bpy.ops.wm.open_mainfile(filepath=BLEND)
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ob = max([o for o in bpy.data.objects if o.type == 'MESH'], key=lambda o: len(o.data.vertices))
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me = ob.data
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n_v, n_l, n_f = len(me.vertices), len(me.loops), len(me.polygons)
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loops_v = np.empty(n_l, dtype=np.int32); me.loops.foreach_get("vertex_index", loops_v)
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co = np.empty(n_v * 3); me.vertices.foreach_get("co", co); co = co.reshape(-1, 3)
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ls = np.empty(n_f, dtype=np.int32); me.polygons.foreach_get("loop_start", ls)
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lt = np.empty(n_f, dtype=np.int32); me.polygons.foreach_get("loop_total", lt)
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li = ls[lt == 3]
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IDX = np.stack([li, li + 1, li + 2], axis=1)
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def uv_of(name):
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a = np.empty(n_l * 2)
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me.uv_layers[name].data.foreach_get("uv", a)
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return a.reshape(-1, 2)
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UN = uv_of("UVMap_atlas")
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UO = uv_of("UVMap_tripo")
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print(f"UVMap_atlas RAW range: u {UN[:,0].min():.4f}..{UN[:,0].max():.4f} "
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f"v {UN[:,1].min():.4f}..{UN[:,1].max():.4f}")
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print(f"UVMap_tripo RAW range: u {UO[:,0].min():.4f}..{UO[:,0].max():.4f} "
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f"v {UO[:,1].min():.4f}..{UO[:,1].max():.4f}")
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out01 = ((UN[:, 0] < -1e-6) | (UN[:, 0] > 1 + 1e-6)
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| (UN[:, 1] < -1e-6) | (UN[:, 1] > 1 + 1e-6))
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print(f"loops with UVMap_atlas OUTSIDE [0,1]: {int(out01.sum())} of {n_l} "
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f"({100.0*out01.mean():.2f}%)")
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W = 4096
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Pn_raw = UN[IDX]
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Pn_clip = np.clip(Pn_raw, 0, 1)
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def uvarea(P):
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return 0.5 * np.abs((P[:, 1, 0] - P[:, 0, 0]) * (P[:, 2, 1] - P[:, 0, 1])
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- (P[:, 2, 0] - P[:, 0, 0]) * (P[:, 1, 1] - P[:, 0, 1]))
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ar_raw = uvarea(Pn_raw) * W * W # in texels
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ar_clip = uvarea(Pn_clip) * W * W
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P3 = co[loops_v[IDX]]
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a3 = 0.5 * np.linalg.norm(np.cross(P3[:, 1] - P3[:, 0], P3[:, 2] - P3[:, 0]), axis=1)
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UNITM = 1.777 / (co[:, 2].max() - co[:, 2].min())
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cm2 = a3 * UNITM * UNITM * 1e4
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tiny_raw = ar_raw < 0.5
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killed_by_clip = (ar_raw >= 0.5) & (ar_clip < 0.5)
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print(f"\ntriangles with <0.5 texel of NEW uv area (before clipping): {int(tiny_raw.sum())} "
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f"holding {cm2[tiny_raw].sum():.1f} cm2")
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print(f"triangles that had area but LOSE it to [0,1] clipping: "
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f"{int(killed_by_clip.sum())} holding {cm2[killed_by_clip].sum():.1f} cm2")
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bad = tiny_raw | killed_by_clip
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print(f"\ntotal suspect: {int(bad.sum())} triangles, {cm2[bad].sum():.1f} cm2 "
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f"({100.0*cm2[bad].sum()/cm2.sum():.2f}% of surface)")
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if bad.any():
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cen = P3[bad].mean(axis=1)
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z = (cen[:, 2] - co[:, 2].min()) / (co[:, 2].max() - co[:, 2].min())
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print(" height distribution of the suspect faces (u = fraction of body height):")
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hist, ed = np.histogram(z, bins=10, range=(0, 1))
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for c, l_, h_ in zip(hist, ed[:-1], ed[1:]):
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if c:
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print(f" u {l_:.1f}-{h_:.1f}: {c:5d}")
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print(f" their source-atlas uv area: median {np.median(uvarea(UO[IDX][bad])*W*W):.2f} texels "
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f"(all triangles: {np.median(uvarea(UO[IDX])*W*W):.2f})")
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# Are they degenerate in 3D as well, or real surface?
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print(f"\n3D area of suspect faces: median {np.median(cm2[bad]):.4f} cm2 vs "
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f"{np.median(cm2):.4f} cm2 for all faces")
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# At the reported uniform 2.2 px/mm a 0.11 cm2 face should get ~53 texels, not <0.5. So the
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# density is NOT uniform across all islands — only across the big ones that got reported.
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# Measure it per island, over every island.
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Q = 1 << 20
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k = (loops_v.astype(np.int64) * Q * Q
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+ np.round(np.clip(UN[:, 0], 0, 1) * (Q - 1)).astype(np.int64) * Q
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+ np.round(np.clip(UN[:, 1], 0, 1) * (Q - 1)).astype(np.int64))
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_, uvv = np.unique(k, return_inverse=True)
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n_uvv = uvv.max() + 1
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T = np.stack([uvv[li], uvv[li + 1], uvv[li + 2]], axis=1)
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par = np.arange(n_uvv, dtype=np.int64)
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def find(x):
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r = x
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while par[r] != r:
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r = par[r]
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while par[x] != r:
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par[x], x = r, par[x]
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return r
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for a_, b_, c_ in T:
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ra, rb, rc = find(a_), find(b_), find(c_)
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if ra != rb:
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par[rb] = ra
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if ra != rc:
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par[rc] = ra
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_, isl = np.unique(np.array([find(i) for i in range(n_uvv)]), return_inverse=True)
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fisl = isl[T[:, 0]]
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n_isl = isl.max() + 1
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iuv = np.bincount(fisl, weights=uvarea(Pn_clip), minlength=n_isl)
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i3d = np.bincount(fisl, weights=a3, minlength=n_isl)
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inf_ = np.bincount(fisl, minlength=n_isl)
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UN_M = UNITM
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dens = np.where(i3d > 0, np.sqrt(np.maximum(iuv, 0) / np.maximum(i3d, 1e-20))
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* W / (UN_M * 1000.0), np.nan)
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print(f"\n=== PER-ISLAND TEXEL DENSITY, all {n_isl} islands (px/mm) ===")
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fd = dens[np.isfinite(dens)]
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for p in (1, 5, 25, 50, 75, 95, 99):
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print(f" p{p:<2d} {np.percentile(fd, p):.4f}")
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low = np.isfinite(dens) & (dens < 0.5)
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print(f" islands under 0.5 px/mm: {int(low.sum())} of {n_isl}, holding "
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f"{(i3d[low]*UN_M*UN_M*1e4).sum():.1f} cm2 "
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f"({100.0*i3d[low].sum()/i3d.sum():.2f}% of surface) in {int(inf_[low].sum())} faces")
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big = np.isfinite(dens) & (dens > 1.5)
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print(f" islands over 1.5 px/mm: {int(big.sum())} holding "
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f"{100.0*i3d[big].sum()/i3d.sum():.2f}% of surface")
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print("SKIPPROBE_DONE")
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