Sweep possible now for key
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+53
-60
@@ -4847,71 +4847,63 @@ def _grade_write_manifest(out_dir: Path, manifest: dict) -> Path:
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def _stage_key(project_path, filters, ref, out_dir, source_name, ss) -> int:
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"""Auto matte search (objective) → one recommended candidate + manifest.
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Coordinate descent over the matte fields, minimising 'partial' (unresolved
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green fringe) subject to keeping the subject opaque — a candidate that drops
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the opaque fraction below baseline (over-keying eats the subject) is rejected.
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"""
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def clamp(v, lo, hi):
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return max(lo, min(hi, v))
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"""Deterministic aggressiveness sweep → 10 matte variants to pick from.
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An objective search always prefers the most aggressive key (lowest fringe),
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which erodes edges and eats low-saturation subject pixels (e.g. eyes go
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transparent/magenta). So instead of auto-picking, this ramps the three
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eroding matte knobs together — screen_gain, shadow_boost, clip_black — from
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gentle (subject fully intact, maybe faint background residue) to aggressive
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(background gone but subject eroding), and lets the eye judge. The opaque
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column falls as the key eats the subject; pick the balance before that."""
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base = _grade_step(filters, "gnommokey")
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cur = dict(base)
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bt, bo, bp = _eval_alpha(ref, _mask_and(filters, cur))
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floor = bo * 0.98
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print(f" Baseline: transparent {bt*100:.1f}% opaque {bo*100:.1f}% partial {bp*100:.1f}%")
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g0, b0 = float(cur.get("screen_gain", 100)), float(cur.get("screen_balance", 50))
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grids = {
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"screen_gain": sorted({int(clamp(g0 * f, 80, 300)) for f in (0.7, 0.85, 1.0, 1.2, 1.4, 1.7)}),
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"screen_balance": sorted({int(clamp(b0 + d, 0, 100)) for d in (-20, -10, 0, 10, 20)}),
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"shadow_boost": [0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0],
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"clip_black": [0, 2, 4, 6, 8, 10, 12],
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}
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def better(cand, best):
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ct, co, cp = cand
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bt_, bo_, bp_ = best
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cok, bok = co >= floor, bo_ >= floor
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if cok != bok:
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return cok
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if abs(cp - bp_) > 1e-6:
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return cp < bp_
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return ct > bt_
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best = (bt, bo, bp)
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for _ in range(2):
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for param, values in grids.items():
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lb_cfg, lb = dict(cur), best
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for v in values:
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cand = dict(cur)
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cand[param] = v
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s = _eval_alpha(ref, _mask_and(filters, cand))
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if better(s, lb):
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lb, lb_cfg = s, cand
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cur, best = lb_cfg, lb
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ft, fo, fp = best
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params = {k: cur[k] for k in ("screen_gain", "screen_balance", "shadow_boost", "clip_black") if k in cur}
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png = out_dir / "key_1.png"
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_render_preview(ref, _mask_and(filters, cur), png)
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steps = [round(i / 9, 2) for i in range(10)] # aggressiveness 0.0 .. 1.0
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print(" Sweeping key aggressiveness 0.0 → 1.0 (gain 120→280, shadow_boost 0→3, clip_black 0→12)")
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candidates = []
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for i, a in enumerate(steps, 1):
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params = {
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"screen_gain": int(round(120 + 160 * a)),
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"shadow_boost": round(3.0 * a, 2),
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"clip_black": int(round(12 * a)),
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}
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cfg = dict(base, **params)
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t, o, p = _eval_alpha(ref, _mask_and(filters, cfg))
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png = out_dir / f"key_{i}.png"
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_render_preview(ref, _mask_and(filters, cfg), png)
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params["aggressiveness"] = a
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candidates.append({
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"id": f"key_{i}", "file": png.name, "params": params,
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"hint": {"transparent_pct": round(t * 100, 1),
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"opaque_pct": round(o * 100, 1),
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"partial_pct": round(p * 100, 1)},
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})
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# Recommend the *gentlest* setting that has essentially cleared the background
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# — the knee where transparency stops climbing. Past it, more aggression just
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# erodes the subject, which is exactly what we're trying to avoid.
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rec = candidates[len(candidates) // 3]["id"]
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for i in range(1, len(candidates)):
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dt = candidates[i]["hint"]["transparent_pct"] - candidates[i - 1]["hint"]["transparent_pct"]
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if dt < 0.3:
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rec = candidates[i - 1]["id"]
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break
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manifest = {
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"stage": "key", "target_step": "gnommokey",
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"source": source_name, "ss": round(ss, 2), "swept": list(params.keys()),
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"recommended": "key_1",
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"candidates": [{
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"id": "key_1", "file": png.name, "params": params,
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"hint": {"transparent_pct": round(ft * 100, 1), "partial_pct": round(fp * 100, 1)},
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}],
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"source": source_name, "ss": round(ss, 2),
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"swept": ["screen_gain", "shadow_boost", "clip_black"],
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"recommended": rec, "candidates": candidates,
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}
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mpath = _grade_write_manifest(out_dir, manifest)
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print(f"\n Selected (partial {bp*100:.1f}% → {fp*100:.1f}%, subject held at {fo*100:.1f}%):")
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for k, v in params.items():
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print(f" {k}: {base.get(k, '—')} → {v}")
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print(f" Preview: {png}")
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print(f" {'id':>8} {'aggr':>5} {'gain':>4} {'shadow':>6} {'transp':>7} {'opaque':>7} {'partial':>7} png")
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print(f" {'-'*8} {'-'*5} {'-'*4} {'-'*6} {'-'*7} {'-'*7} {'-'*7} {'-'*3}")
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for c in candidates:
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star = " ◀ suggested" if c["id"] == rec else ""
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pr, h = c["params"], c["hint"]
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print(f" {c['id']:>8} {pr['aggressiveness']:>5} {pr['screen_gain']:>4} {pr['shadow_boost']:>6} "
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f"{h['transparent_pct']:>6}% {h['opaque_pct']:>6}% {h['partial_pct']:>6}% {c['file']}{star}")
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print("\n opaque falls as the key eats the subject (eroded edges, keyed eyes) — pick just before that.")
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print(f" Manifest: {mpath}")
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print(f" Apply: gnommo -p {project_path.name} grade --pick key_1")
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print(" Pick the gentlest variant that clears the background without eroding the head/eyes:")
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print(f" gnommo -p {project_path.name} grade --pick key_4")
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return 0
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@@ -5040,8 +5032,9 @@ def _grade_pick(project_path, stage_hint, pick) -> int:
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if cand is None:
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print(f" ERROR: candidate '{cand_id}' not in {mpath.name}.")
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return 1
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# 'look'/'paleness' are UI-only dials, not real color_grade fields.
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params = {k: v for k, v in cand["params"].items() if k not in ("look", "paleness")}
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# 'look'/'paleness'/'aggressiveness' are UI-only dials, not real fields.
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params = {k: v for k, v in cand["params"].items()
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if k not in ("look", "paleness", "aggressiveness")}
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_apply_candidate_to_project(project_path, manifest["target_step"], params)
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print(f" Applied {cand_id} → project.json ({manifest['target_step']}): "
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+ ", ".join(f"{k}={v}" for k, v in params.items()))
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