jeremy
3d8825f5a9
REGISTRY rewritten around the central rule: a character folder is born only when a body ships to ariki-game (<character>_base_v<NN> = ship ordinal). lena_nude dissolves accordingly: - characters/female/lena_base_v01/ — SHIPPED 2026-08-10: AccuRig GLB carrier, T-pose/rig FBX + JSON, previews, frozen README - characters/work/lena/ — the live lane: recipes 01-47 (incl. new 36-47: refill/sheets/clay/despeckle/musculature/spin/AccuRig export/graft/pose QC), masters (athletic_v04 blend + textures, accurig blend), lane-history README - hires_claude/hires_work intermediates (blends, logs, probes) pruned Supporting docs: AGENTS.md, working-files rule, rig-graft plan addendum, originals README, prune_lane.py. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
81 lines
3.0 KiB
Python
81 lines
3.0 KiB
Python
# Stage 34 (read-only): measure the APPROVED concept turnaround against our body, in the same
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# units, so "uniform skin" stops being an adjective.
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#
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# blender --background --python 34_target_tone.py -- <concept_dir> <our_render.png>
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#
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# Both inputs are renders of a body on a flat grey background, so the comparison is like for like.
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# Redness (r-g) is the useful statistic: it barely moves with lighting, so a body lit by one light
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# should hold it nearly constant. Lena's Tripo texture does not — her feet measure 50% redder than
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# her belly — and the question is what the approved reference does.
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import bpy, sys, os
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import numpy as np
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argv = sys.argv[sys.argv.index("--") + 1:]
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CONCEPT_DIR, OURS = argv[0], argv[1]
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def load(p):
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im = bpy.data.images.load(p)
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w, h = im.size
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b = np.empty(w * h * 4, dtype=np.float32)
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im.pixels.foreach_get(b)
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a = b.reshape(h, w, 4)[:, :, :3].copy()
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bpy.data.images.remove(im)
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return a[::-1] # Blender rows are bottom-up; flip to image order
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def body_mask(A):
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# background is flat and desaturated; skin is not
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sat = A.max(axis=2) - A.min(axis=2)
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return (sat > 0.06) & (A.max(axis=2) > 0.15)
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def report(name, A):
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m = body_mask(A)
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if m.sum() < 500:
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print(f"{name}: no body found")
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return
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ys, xs = np.nonzero(m)
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y0, y1 = ys.min(), ys.max()
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rg = (A[:, :, 0] - A[:, :, 1])
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luma = A.mean(axis=2)
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print(f"\n=== {name} === {m.sum()} body pixels, rows {y0}..{y1}")
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print(f" WHOLE BODY r-g mean {rg[m].mean():.3f} std {rg[m].std():.3f} "
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f"luma mean {luma[m].mean():.3f}")
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# slice by height: 0 = top of the figure (head), 1 = bottom (feet)
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print(" by height band (0=head .. 1=feet):")
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rows = []
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for i in range(10):
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a = y0 + (y1 - y0) * i / 10.0
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b = y0 + (y1 - y0) * (i + 1) / 10.0
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band = np.zeros_like(m)
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band[int(a):int(b) + 1, :] = True
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mm = m & band
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if mm.sum() < 200:
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continue
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rows.append((i / 10.0, rg[mm].mean(), luma[mm].mean(), int(mm.sum())))
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print(f" {i/10.0:.1f}-{(i+1)/10.0:.1f} r-g {rg[mm].mean():.3f} "
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f"luma {luma[mm].mean():.3f} n={int(mm.sum())}")
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if rows:
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arr = np.array([r[1] for r in rows])
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print(f" SPREAD of r-g across height bands: {arr.max()-arr.min():.3f} "
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f"(min {arr.min():.3f} at {rows[int(np.argmin(arr))][0]:.1f}, "
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f"max {arr.max():.3f} at {rows[int(np.argmax(arr))][0]:.1f})")
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return rg[m], luma[m]
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res = {}
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for f in sorted(os.listdir(CONCEPT_DIR)):
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if f.lower().endswith(".png"):
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res[f] = report("CONCEPT " + f, load(os.path.join(CONCEPT_DIR, f)))
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ours = report("OURS " + os.path.basename(OURS), load(OURS))
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print("\n" + "=" * 72)
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print("VERDICT — how much does redness vary over the body?")
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for k, v in res.items():
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if v:
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print(f" concept {k:<32} r-g std {v[0].std():.4f}")
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if ours:
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print(f" ours {os.path.basename(OURS):<32} r-g std {ours[0].std():.4f}")
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print("TARGET_TONE_DONE")
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