Recognizion with multiple

programs/readTwoImages.py

@@ -324,7 +324,12 @@ def main():
     ids1 = ids1.flatten().tolist()
     ids2 = ids2.flatten().tolist()
 
-    
+    # Neu: merken, welche Kamera welchen Marker gesehen hat
+    seen_by = {}  # id -> 1, 2 oder 3 (3 = beide)
+    for mid in ids1:
+        seen_by[mid] = seen_by.get(mid, 0) | 1
+    for mid in ids2:
+        seen_by[mid] = seen_by.get(mid, 0) | 2
 
     # Build dicts: id -> corners, center, rvec/tvec (per-camera PnP)
     def build_marker_dict(img, corners_list, ids, K, D, draw = False) -> Tuple[Dict[int,np.ndarray], Dict[int,np.ndarray], Dict[int,Tuple[np.ndarray,np.ndarray]]]:
@@ -411,7 +416,7 @@ def main():
     # Collect markers seen by at least one camera
     all_ids = set(ids1) | set(ids2)
     # Output structures
-    rows = [("id", "x_mm", "y_mm", "z_mm", "roll_deg", "pitch_deg", "yaw_deg")]
+    rows = [("id", "x_mm", "y_mm", "z_mm", "roll_deg", "pitch_deg", "yaw_deg", "seen_by")]
     marker_list = []
 
     # Camera orientations in Euler (ZYX)
@@ -473,7 +478,7 @@ def main():
             continue
         roll, pitch, yaw = orientation_in_machine(mid)
         x_mm, y_mm, z_mm = (X_mach * 1000.0).tolist()
-        rows.append((mid, f"{x_mm:.2f}", f"{y_mm:.2f}", f"{z_mm:.2f}", f"{roll:.3f}", f"{pitch:.3f}", f"{yaw:.3f}"))
+        rows.append((mid, f"{x_mm:.2f}", f"{y_mm:.2f}", f"{z_mm:.2f}", f"{roll:.3f}", f"{pitch:.3f}", f"{yaw:.3f}", seen_by.get(mid, 0)))
         marker_list.append({
             "id": int(mid),
             "position_mm": [float(x_mm), float(y_mm), float(z_mm)],