feat(captcha): 增加全题型图片落盘、字形一致性强校验与防秒换拟人交互机制

- 题目图片自动下载: 所有题型原图统一落盘至 scratch/captcha_debug，文字点选自动生成带编号红圈标注图便于肉眼核验
- 字形严格一致性校验: 在 SolveResult 增加 text_match_ok 检查，对图字不符或混淆干扰题直接拒答换题，避免错答引发 errorCode=12
- 防秒换与拟人延时: 遇到非预期题目换题等待 2.8~4.2s (对齐 HAR 真实抓包)，求解失败等待 2.5~3.8s，作答前模拟交互 5.5~7.5s
- 代理容错增强: 在 OneMsAdapter 捕获代理断流与鉴权异常，支持动态轮换新代理重试

tcaptcha/glyph_solver.py

@@ -119,9 +119,29 @@ class SolveResult:
         self.posterior = posterior
         self.assignments = assignments
 
+    @property
+    def text_match_ok(self) -> bool:
+        """检查指派的每个字形直接 OCR 文本是否与目标汉字一致 (杜绝图字不符或混淆干扰字盲猜提交)"""
+        if not self.assignments or len(self.assignments) != len(self.targets):
+            return False
+        for ti, g in enumerate(self.assignments):
+            target_char = self.targets[ti]
+            ocr_char = self.glyphs[g].ocr_text
+            if ocr_char and target_char not in ocr_char:
+                return False
+        return True
+
     @property
     def ok(self) -> bool:
-        return len(self.points) == len(self.targets) and len(self.points) > 0
+        return (len(self.points) == len(self.targets)
+                and len(self.points) > 0
+                and self.text_match_ok)
+
+    @property
+    def min_target_score(self) -> float:
+        if not self.assignments or self.score_matrix is None:
+            return 0.0
+        return min(float(self.score_matrix[g, ti]) for ti, g in enumerate(self.assignments))
 
     def describe(self) -> str:
         detail = ", ".join(
@@ -129,7 +149,8 @@ class SolveResult:
             f"({self.score_matrix[g, ti]:.3f})"
             for ti, (t, g) in enumerate(zip(self.targets, self.assignments))
         )
-        return f"posterior={self.posterior:.3f} [{detail}]"
+        status = "ALL_MATCHED" if self.text_match_ok else "MISMATCH"
+        return f"status={status} posterior={self.posterior:.3f} [{detail}]"
 
 
 class TextClickSolver:
@@ -182,7 +203,31 @@ class TextClickSolver:
                 continue
             glyphs.append(Glyph(x0, y0, x1, y1,
                                 (sub[y0:y1 + 1, x0:x1 + 1] * 255).astype(np.uint8)))
-        # 阅读顺序排序 (先上后下, 再左后右) —— 仅用于结果稳定
+        glyphs.sort(key=lambda g: (g.y0 // 64, g.x0))
+        return glyphs
+
+    def detect_glyphs_relaxed(self, image: bytes | np.ndarray | Image.Image) -> List[Glyph]:
+        """放宽阈值的备用分割, 防止汉字偏暗或面积偏小导致的漏检"""
+        bgr = self._to_bgr(image)
+        hsv = cv2.cvtColor(bgr, cv2.COLOR_BGR2HSV)
+        mask = cv2.inRange(hsv, np.array((8, 85, 135), np.uint8), np.array((45, 255, 255), np.uint8))
+        mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5)))
+        dilated = cv2.dilate(mask, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (MERGE_KERNEL, MERGE_KERNEL)))
+        count, labels, stats, _ = cv2.connectedComponentsWithStats(dilated)
+
+        glyphs: List[Glyph] = []
+        for i in range(1, count):
+            if stats[i, cv2.CC_STAT_AREA] < 350:
+                continue
+            sub = ((labels == i) & (mask > 0))
+            ys, xs = np.nonzero(sub)
+            if len(xs) == 0:
+                continue
+            x0, y0, x1, y1 = int(xs.min()), int(ys.min()), int(xs.max()), int(ys.max())
+            w, h = x1 - x0 + 1, y1 - y0 + 1
+            if not (0.28 <= w / h <= 3.5) or w < 18 or h < 18:
+                continue
+            glyphs.append(Glyph(x0, y0, x1, y1, (sub[y0:y1 + 1, x0:x1 + 1] * 255).astype(np.uint8)))
         glyphs.sort(key=lambda g: (g.y0 // 64, g.x0))
         return glyphs
 
@@ -231,6 +276,8 @@ class TextClickSolver:
 
         for attempt in range(retries):
             glyphs = self.detect_glyphs(image)
+            if len(glyphs) < len(targets):
+                glyphs = self.detect_glyphs_relaxed(image)
             if len(glyphs) < len(targets):
                 logger.warning("第 %d 次: 检出字形 %d 个 < 目标 %d 个",
                                attempt + 1, len(glyphs), len(targets))