fix(camera): lower frontal and side confidence thresholds

h5/js/capture-quality.js

@@ -6,7 +6,7 @@
   'use strict';
   // Real-phone feedback: ease alignment and normal hand/head movement while
   // retaining two checked frames, one face, framing and final JPEG validation.
-  var config = Object.freeze({ version: '2026-10-16-front-detection-v8', score: 0.4, frontScore: 0.3,
+  var config = Object.freeze({ version: '2026-10-16-confidence-v9', score: 0.3, frontScore: 0.25,
     near: 0.30, far: 0.68, center: 0.16, edge: 0.01,
     dark: 110, bright: 220, holdMs: 450, minFrames: 2, maxGapMs: 2000,
     yawDrift: 8, pitchDrift: 8, centerDrift: 0.055, sizeDrift: 0.065 });

h5/test/customer-feedback-fourth.js

@@ -73,11 +73,12 @@ for (const changes of [{ height: 179 }, { height: 410 }, { x: -10 }, { y: 5 }])
   const d = face(); Object.assign(d.detection.box, changes); assert(!check(d).ok);
 }
 const weak = face(); weak.detection.score = .45; assert(check(weak).ok);
-for(const score of [.3,.35,.3999]){const d=face();d.detection.score=score;assert(check(d).ok,'relaxed front confidence');}
-const low=face();low.detection.score=.2999;assert.equal(check(low).hint,'请保持面部清晰');
-for(const target of ['left','right']){const d=face(target==='left'?-45:45);d.detection.score=.35;assert.equal(check(d,{target}).hint,'请保持面部清晰');d.detection.score=.4;assert(check(d,{target}).ok);}
-assert.equal(Quality.scoreThreshold('front'),.3);assert.equal(Quality.scoreThreshold('left'),.4);assert.equal(Quality.scoreThreshold('right'),.4);
-weak.detection.score = .29; assert(!check(weak).ok);
+for(const score of [.25,.29,.3,.35,.3999]){const d=face();d.detection.score=score;assert(check(d).ok,'relaxed front confidence');}
+const low=face();low.detection.score=.2499;assert.equal(check(low).hint,'请保持面部清晰');
+for(const target of ['left','right']){const d=face(target==='left'?-45:45);d.detection.score=.2999;assert.equal(check(d,{target}).hint,'请保持面部清晰');for(const score of [.3,.35,.4]){d.detection.score=score;assert(check(d,{target}).ok);}}
+assert.equal(Quality.scoreThreshold('front'),.25);assert.equal(Quality.scoreThreshold('left'),.3);assert.equal(Quality.scoreThreshold('right'),.3);
+for(const target of ['front','left','right']) for(const score of [0,-1,NaN,Infinity]){const d=face(target==='front'?0:target==='left'?-45:45);d.detection.score=score;assert.equal(check(d,{target}).hint,'请保持面部清晰');}
+weak.detection.score = .24; assert(!check(weak).ok);
 const obs = check(face()).observation;
 let held = Quality.hold(null, obs, 1000); assert(!held.ready);
 held = Quality.hold(held.state, obs, 1400); assert(!held.ready);
@@ -120,7 +121,7 @@ assert.equal(Diagnostics.assess(raw).views.right.status, 'valid');
 const normalized = Diagnostics.normalize({ version: Quality.config.version, secret: 'discard', views: { front: { mode: 'live', yaw: 1, score: .9, luma: Infinity, secret: 'discard' }, left: { mode: 'unchecked', reason: 'model-unavailable' } } });
 assert.equal(normalized.policy.capture.holdMs, 450);
 assert.equal(normalized.policy.capture.minFrames, 2);
-assert.equal(normalized.version, '2026-10-16-front-detection-v8');
+assert.equal(normalized.version, '2026-10-16-confidence-v9');
 assert.equal(normalized.views.front.luma, undefined);
 assert(!JSON.stringify(normalized).includes('discard'));
 assert.equal(Diagnostics.normalize({ version: '<script>' }).version, 'unknown');