Add slide and rotate interactive captcha solvers

New solver subsystem with independent models:
- GapDetectorCNN (1x128x256 grayscale → sigmoid) for slide gap detection
- RotationRegressor (3x128x128 RGB → sin/cos via tanh) for rotation angle prediction
- SlideSolver with 3-tier strategy: template match → edge detect → CNN fallback
- RotateSolver with ONNX sin/cos → atan2 inference
- Generators, training scripts, CLI commands, and slide track utility

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

inference/export_onnx.py

@@ -18,11 +18,14 @@ from config import (
     THREED_CHARS,
     NUM_CAPTCHA_TYPES,
     REGRESSION_RANGE,
+    SOLVER_CONFIG,
 )
 from models.classifier import CaptchaClassifier
 from models.lite_crnn import LiteCRNN
 from models.threed_cnn import ThreeDCNN
 from models.regression_cnn import RegressionCNN
+from models.gap_detector import GapDetectorCNN
+from models.rotation_regressor import RotationRegressor
 
 
 def export_model(
@@ -52,7 +55,7 @@ def export_model(
     dummy = torch.randn(1, *input_shape)
 
     # 分类器和识别器的 dynamic_axes 不同
-    if model_name == "classifier" or model_name in ("threed_rotate", "threed_slider"):
+    if model_name == "classifier" or model_name in ("threed_rotate", "threed_slider", "gap_detector", "rotation_regressor"):
         dynamic_axes = {"input": {0: "batch"}, "output": {0: "batch"}}
     else:
         # CTC 模型: output shape = (T, B, C)
@@ -110,6 +113,14 @@ def _load_and_export(model_name: str):
         h, w = IMAGE_SIZE["3d_slider"]
         model = RegressionCNN(img_h=h, img_w=w)
         input_shape = (1, h, w)
+    elif model_name == "gap_detector":
+        h, w = SOLVER_CONFIG["slide"]["cnn_input_size"]
+        model = GapDetectorCNN(img_h=h, img_w=w)
+        input_shape = (1, h, w)
+    elif model_name == "rotation_regressor":
+        h, w = SOLVER_CONFIG["rotate"]["input_size"]
+        model = RotationRegressor(img_h=h, img_w=w)
+        input_shape = (3, h, w)
     else:
         print(f"[错误] 未知模型: {model_name}")
         return
@@ -119,11 +130,15 @@ def _load_and_export(model_name: str):
 
 
 def export_all():
-    """依次导出 classifier, normal, math, threed_text, threed_rotate, threed_slider 六个模型。"""
+    """依次导出全部模型 (含 solver 模型)。"""
     print("=" * 50)
     print("导出全部 ONNX 模型")
     print("=" * 50)
-    for name in ["classifier", "normal", "math", "threed_text", "threed_rotate", "threed_slider"]:
+    for name in [
+        "classifier", "normal", "math", "threed_text",
+        "threed_rotate", "threed_slider",
+        "gap_detector", "rotation_regressor",
+    ]:
         _load_and_export(name)
     print("\n全部导出完成。")