"""Model-free tests of the pose geometry and the scan state machine. Run: python -m tests.test_logic""" import time from types import SimpleNamespace import numpy as np from app.config import settings as S from app.quality import Analysis, head_pose, quality_problem from app.session import FAIL_GENERIC, ScanSession, State from app.store import Match def good(yaw=0.0, cx=0.5, cy=0.5, **kw) -> Analysis: a = Analysis(frame_w=640, frame_h=480, n_faces=1, bbox=(640 * (cx - 0.2), 480 * (cy - 0.3), 640 * (cx + 0.2), 480 * (cy + 0.3)), kps=None, det_score=0.9, yaw=yaw, pitch=0.62, roll=0.0, blur=120, brightness=120, contrast=50) for k, v in kw.items(): setattr(a, k, v) return a class FakeEngine: def __init__(self): self.queue = [] def analyze(self, frame): return self.queue.pop(0) def embed(self, frame, a): return np.ones(4, np.float32) / 2 class FakeGallery: """Stands in for the 1:N identification the real Gallery does with face_distance.""" def __init__(self, ok=True): self.ok = ok # does the current face match ANY member at all? self.as_id = "m1" # which member the current face is identified as self.marked = [] def identify(self, q): if not self.ok: return Match(None, None, 0.9) # unknown face (nothing within TOLERANCE) return Match(self.as_id, "Test Member", 0.3, "other", 0.8) def last_attendance_ts(self, member_id): return None def mark_attendance(self, member_id, score, margin, session): self.marked.append(member_id) return "2026-10-12T13:00:00+05:30" def run(sess, ctx, analyses): out = None for a in analyses: ctx.engine.queue.append(a) out = sess.process(None, ctx) return out def make(steps=("left", "right"), ok=True): ctx = SimpleNamespace(engine=FakeEngine(), gallery=FakeGallery(ok), objects=None) return ScanSession("m1", "Test Member", list(steps)), ctx def test_pose_geometry(): # frontal face: nose centred between the eyes le, re, nose, lm, rm = (260, 200), (380, 200), (320, 254), (275, 290), (365, 290) yaw, pitch, roll = head_pose(np.array([le, re, nose, lm, rm], float)) assert abs(yaw) < 1e-6 and 0.5 < pitch < 0.7 and abs(roll) < 1e-6 # nose shifted toward image-right => user turned toward THEIR left => positive yaw yaw_l, _, _ = head_pose(np.array([le, re, (350, 254), lm, rm], float)) assert yaw_l > 0.2 # flat photo rotated about vertical axis: all x shrink uniformly -> yaw proxy unchanged shrink = lambda p: (320 + (p[0] - 320) * 0.7, p[1]) yaw_p, _, _ = head_pose(np.array([shrink(p) for p in (le, re, nose, lm, rm)], float)) assert abs(yaw_p) < 1e-6 def test_gates(): assert quality_problem(good()) is None assert "closer" in quality_problem(good(bbox=(300, 220, 340, 260))) assert quality_problem(Analysis(n_faces=2)).startswith("Only one") assert "Look straight" in quality_problem(good(yaw=0.3)) assert "blurry" in quality_problem(good(blur=5)) assert "Too dark" in quality_problem(good(brightness=20)) assert "Hold still" in quality_problem(good(cx=0.58), prev_center=(0.5, 0.5)) assert quality_problem(good(yaw=0.2), strict=False) is None # enrolment allows slight turns def test_happy_path(): sess, ctx = make() n = S.stable_frames out = run(sess, ctx, [good()] * n) assert sess.state == State.CHALLENGE, out # steps are left then right; yaw > 0 is "left" out = run(sess, ctx, [good(yaw=0.0), good(yaw=0.3), good(yaw=0.05)]) assert sess.step_idx == 1, out out = run(sess, ctx, [good(yaw=-0.3), good(yaw=0.0)]) assert sess.state == State.VERIFYING, out out = run(sess, ctx, [good()] * n) assert sess.state == State.MARKED and out["member"]["id"] == "m1" and ctx.gallery.marked == ["m1"] assert out["confidence"] > 0 # identification confidence is returned assert "score" not in out # raw scores must not reach the client def test_no_challenge_flow_is_fast(): sess, ctx = make(steps=[]) # CHALLENGE_STEPS=0 disables the liveness challenge out = run(sess, ctx, [good()] * S.stable_frames) assert sess.state == State.VERIFYING, out # straight from positioning to verifying out = run(sess, ctx, [good()] * S.stable_frames) assert sess.state == State.MARKED and ctx.gallery.marked == ["m1"] def test_wrong_direction_does_not_advance(): sess, ctx = make(steps=("left",)) run(sess, ctx, [good()] * S.stable_frames) out = run(sess, ctx, [good(yaw=-0.35)] * 5) # turned RIGHT when LEFT was asked assert sess.step_idx == 0 and sess.step_phase == "turn" and "Other way" in out["message"] def test_photo_never_passes_liveness(): sess, ctx = make(steps=("left",)) run(sess, ctx, [good()] * S.stable_frames) run(sess, ctx, [good(yaw=0.0)] * 20) # a flat photo: yaw proxy stays ~0 assert sess.state == State.CHALLENGE sess.challenge_started = time.monotonic() - S.challenge_timeout_s - 1 ctx.engine.queue.append(good()) out = sess.process(None, ctx) assert sess.state == State.FAILED and "timed out" in out["message"] def test_identity_mismatch_fails_and_is_counted(): sess, ctx = make(ok=False) out = run(sess, ctx, [good()] * S.stable_frames) assert sess.state == State.FAILED and out["message"] == FAIL_GENERIC and sess.verification_failed def test_swap_after_challenge_is_caught(): sess, ctx = make(steps=("left",)) run(sess, ctx, [good()] * S.stable_frames) # real member identified and adopted run(sess, ctx, [good(yaw=0.3), good(yaw=0.0)]) assert sess.state == State.VERIFYING and sess.member_id == "m1" ctx.gallery.as_id = "m2" # a different person finishes the scan out = run(sess, ctx, [good()] * S.stable_frames) assert sess.state == State.FAILED and not ctx.gallery.marked def test_broken_stability_window_resets(): sess, ctx = make() run(sess, ctx, [good()] * (S.stable_frames - 1)) out = run(sess, ctx, [good(blur=1)]) # one bad frame assert sess.good_streak == 0 and sess.pre_embs == [] and not out["ok"] if __name__ == "__main__": for name, fn in list(globals().items()): if name.startswith("test_"): fn() print("ok ", name) print("all passed")