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last update for a while the exe for this will be 1.2 well i make it!!

Author: natdog400

README.md

@@ -131,8 +131,10 @@ Action dictionary fields (as used across sequences and failsafe steps):
 ## How Matching and Actions Work
 
 - Template matching uses OpenCV (`cv2.matchTemplate`). Confidence threshold is adjustable per step.
-- Feature matching uses ORB descriptors and BF matcher with Lowe's ratio filtering.
-  - Homography via RANSAC estimates rotation/scale; center of the matched polygon is used.
+- Feature matching supports multiple detectors and safe fallbacks:
+  - Detectors: `ORB` (fast), `AKAZE` (scale-robust), `SIFT` (strong features; requires `opencv-contrib-python`).
+  - Pipeline: KNN + Lowe’s ratio → RANSAC homography → sanity check (area ratio) → center of detected polygon.
+  - Fallbacks: If detector fails, automatically tries `AKAZE`, then `SIFT`. If all fail, a multi‑scale template match runs.
   - Provide `strategy: "feature"` and optional `min_inliers`, `ratio_thresh`, `ransac_thresh` per step.
 - If a step has no `find` template, its actions run directly.
 - `move_to` can target the detected position or a random point inside a selected region.
@@ -185,6 +187,9 @@ Action dictionary fields (as used across sequences and failsafe steps):
 
 - Strategy Dropdown: Default (template) or Feature (scale/rotation).
 - Parameters: Min Inliers, Ratio, RANSAC thresholds.
+- Visualizer controls:
+  - Detector: choose `ORB`, `AKAZE`, or `SIFT` for the feature preview.
+  - Show Keypoints: toggle overlay of scene keypoints for visual debugging (off by default for performance).
 - Debug Panel shows:
   - Target screen index, geometry, local capture rect
   - Frame size and bytes-per-line, DPI ratio, pixmap state

bot_gui.py

@@ -2087,6 +2087,18 @@ def init_ui(self):
         params_layout.addWidget(self.ransac_spin)
         form_layout.addRow("Params:", params_layout)
 
+        # Visualizer controls (performance-friendly toggles)
+        viz_layout = QHBoxLayout()
+        self.keypoints_check = QCheckBox("Show Keypoints")
+        self.keypoints_check.setChecked(False)
+        viz_layout.addWidget(self.keypoints_check)
+        viz_layout.addWidget(QLabel("Detector"))
+        self.detector_combo = QComboBox()
+        self.detector_combo.addItems(["ORB", "AKAZE", "SIFT"])
+        viz_layout.addWidget(self.detector_combo)
+        viz_layout.addStretch()
+        form_layout.addRow("Visualizer:", viz_layout)
+
         # Metrics display (move overlay metrics into GUI)
         metrics_layout = QHBoxLayout()
         self.metric_inliers = QLabel("Inliers: -")
@@ -2289,12 +2301,31 @@ def capture_region_bgr(x: int, y: int, w: int, h: int) -> np.ndarray:
             if strategy == "feature":
                 # Feature-based preview: draw inlier matches and polygon
                 try:
-                    orb = cv2.ORB_create(nfeatures=1500)
+                    # Choose detector based on UI (ORB or AKAZE)
+                    use_alg = self.detector_combo.currentText() if hasattr(self, 'detector_combo') else "ORB"
+                    if use_alg == "AKAZE":
+                        detector = cv2.AKAZE_create()
+                        norm = cv2.NORM_HAMMING
+                    elif use_alg == "SIFT":
+                        detector = cv2.SIFT_create()
+                        norm = cv2.NORM_L2
+                    else:
+                        detector = cv2.ORB_create(nfeatures=1500)
+                        norm = cv2.NORM_HAMMING
                     gray_screen = cv2.cvtColor(screenshot, cv2.COLOR_BGR2GRAY)
                     gray_template = cv2.cvtColor(template, cv2.COLOR_BGR2GRAY)
-                    kps1, des1 = orb.detectAndCompute(gray_template, None)
-                    kps2, des2 = orb.detectAndCompute(gray_screen, None)
-                    bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=False)
+                    kps1, des1 = detector.detectAndCompute(gray_template, None)
+                    kps2, des2 = detector.detectAndCompute(gray_screen, None)
+                    # Draw scene keypoints on the preview for visual debugging (optional)
+                    if getattr(self, 'keypoints_check', None) and self.keypoints_check.isChecked():
+                        try:
+                            keypoint_img = cv2.drawKeypoints(display_img, kps2 if kps2 is not None else [], None,
+                                                             color=(255, 255, 0), flags=cv2.DRAW_MATCHES_FLAGS_DEFAULT)
+                            if keypoint_img is not None:
+                                display_img = keypoint_img
+                        except Exception:
+                            pass
+                    bf = cv2.BFMatcher(norm, crossCheck=False)
                     matches = bf.knnMatch(des1, des2, k=2) if des1 is not None and des2 is not None else []
                     good = []
                     ratio_thresh = float(self.ratio_spin.value())