#!/usr/bin/env python3 """Classify face shape candidates from four tape measurements. Only relative comparisons between your four numbers are used, because published face-shape guides state their rules in relative terms. "Roughly equal" uses a single tie band (--tol, default 3%) that is this tool's own parameter, not a figure from any published study. Where measurements alone cannot separate two shapes (e.g. round vs square depends on jaw angle), the tool says so instead of inventing an answer. Usage: python classify_face_shape.py --forehead 14.2 --cheekbones 15.0 \ --jawline 13.6 --length 19.1 [--tol 0.03] [--json] """ from __future__ import annotations import argparse import json import sys WIDTHS = ("forehead", "cheekbones", "jawline") MANUAL_CHECKS = ( "Manual check (a tape cannot see this): " "round vs square needs the jaw angle (soft curve vs strong angle); " "heart vs diamond partly needs chin shape (pointed vs tapered)." ) def make_rules(tol: float): """Rule table: shape -> list of (condition_fn, plain-English condition). The comparisons mirror the rules published in the guide at https://faceshapechart.com/ — stated there in relative terms only. """ def width(m): return max(m[k] for k in WIDTHS) def roughly(a, b, factor=1.0): return abs(a - b) <= tol * factor * max(a, b) def widest_is(key, strict=False): def check(m): w = width(m) if m[key] < w * (1 - tol): # clearly below the widest return False if strict: # must beat the others outright return all(m[key] > m[o] * (1 - tol) for o in WIDTHS if o != key) return True return check return { "oval": [ (widest_is("cheekbones"), "cheekbones widest"), (lambda m: m["length"] > width(m) * (1 + tol * 0.5), "face longer than wide"), (lambda m: m["jawline"] < m["cheekbones"] * (1 - tol * 0.5), "jaw narrower than cheekbones"), ], "round": [ (lambda m: roughly(m["length"], width(m), 1.2), "length roughly equal to width"), (lambda m: roughly(m["forehead"], m["jawline"], 1.5), "forehead roughly equal to jawline"), ], "square": [ (lambda m: roughly(m["forehead"], m["cheekbones"], 1.5) and roughly(m["cheekbones"], m["jawline"], 1.5), "forehead, cheekbones, jawline roughly equal"), (lambda m: roughly(m["length"], width(m), 1.2), "length roughly equal to width"), ], "heart": [ (widest_is("forehead", strict=True), "forehead clearly widest"), (lambda m: m["jawline"] < m["forehead"] * (1 - tol * 0.5), "jaw narrower than forehead"), ], "diamond": [ (widest_is("cheekbones", strict=True), "cheekbones clearly widest"), (lambda m: m["forehead"] < m["cheekbones"] * (1 - tol * 0.5), "forehead narrower than cheekbones"), (lambda m: m["jawline"] < m["cheekbones"] * (1 - tol * 0.5), "jaw narrower than cheekbones"), ], "oblong": [ (lambda m: m["length"] > width(m) * (1 + 4 * tol), "length clearly greater than width"), (lambda m: roughly(m["forehead"], m["cheekbones"], 1.5) and roughly(m["cheekbones"], m["jawline"], 1.5), "forehead, cheekbones, jawline roughly equal"), ], "triangle (pear)": [ (widest_is("jawline", strict=True), "jawline clearly widest"), (lambda m: m["jawline"] > m["cheekbones"] * (1 + tol * 0.5), "jaw wider than cheekbones"), ], "hourglass": [ (lambda m: m["cheekbones"] >= m["forehead"] * (1 - tol) and m["jawline"] > m["forehead"] * (1 - tol) and m["jawline"] >= width(m) * (1 - 2 * tol), "cheekbones AND jawline both prominent"), (lambda m: roughly(m["length"], width(m) * 1.1, 2.0), "length balanced against width"), ], } def classify(m: dict, tol: float): rules = make_rules(tol) results = {} for shape, conds in rules.items(): matched = [text for fn, text in conds if fn(m)] failed = [text for fn, text in conds if not fn(m)] results[shape] = {"score": len(matched), "total": len(conds), "matched": matched, "failed": failed} return results def main() -> int: p = argparse.ArgumentParser(description="Rank face-shape candidates from four measurements.") p.add_argument("--forehead", type=float, required=True, help="widest width across the forehead") p.add_argument("--cheekbones", type=float, required=True, help="widest width across the cheekbones") p.add_argument("--jawline", type=float, required=True, help="width across the jawline") p.add_argument("--length", type=float, required=True, help="hairline-to-chin length") p.add_argument("--tol", type=float, default=0.03, help="tie band for 'roughly equal' as a fraction (default 0.03 = 3%%); this tool's own parameter, not a published figure") p.add_argument("--json", action="store_true", help="print raw JSON") a = p.parse_args() if min(a.forehead, a.cheekbones, a.jawline, a.length) <= 0: p.error("all four measurements must be positive numbers (any consistent unit)") m = {"forehead": a.forehead, "cheekbones": a.cheekbones, "jawline": a.jawline, "length": a.length} results = classify(m, a.tol) if a.json: print(json.dumps({"measurements": m, "tol": a.tol, "results": results}, indent=2)) return 0 ranked = sorted(results.items(), key=lambda kv: (-kv[1]["score"], kv[0])) best = ranked[0][1]["score"] top = [s for s, r in ranked if r["score"] == best] print("Measurements: forehead=%.4g cheekbones=%.4g jawline=%.4g length=%.4g (tol=%.0f%%)" % (a.forehead, a.cheekbones, a.jawline, a.length, a.tol * 100)) print() print("Top candidate(s): %s" % ", ".join(top)) print() for shape, r in ranked: tag = "OK " if not r["failed"] else " " print(" %s[%s] %d/%d matched" % (tag, shape.ljust(16), r["score"], r["total"])) for t in r["matched"]: print(" + %s" % t) for t in r["failed"]: print(" - %s" % t) print() print(MANUAL_CHECKS) return 0 if __name__ == "__main__": sys.exit(main())