From cf184d765c610eba1b2cba8f415d6be4ef1ca6b9 Mon Sep 17 00:00:00 2001
From: appleb_m <martin.appleby@psi.ch>
Date: Fri, 8 May 2026 11:33:42 +0200
Subject: [PATCH] Face_detectrion: service.py tidying up logging, changed
 status of some mesages form infor to debug.

---
 .../daq/operations/face_detection/service.py  | 26 +++++++++----------
 1 file changed, 13 insertions(+), 13 deletions(-)

diff --git a/src/aare/daq/operations/face_detection/service.py b/src/aare/daq/operations/face_detection/service.py
index eafe0f9c..5a608973 100644
--- a/src/aare/daq/operations/face_detection/service.py
+++ b/src/aare/daq/operations/face_detection/service.py
@@ -70,7 +70,7 @@ class FaceDetectionService:
             self.ctx.devs.lamp_light = 2.5
 
             zoom_value = self.ctx.devs.zoom
-            self.logger.info("face detection sequence")
+            self.logger.info("Starting face detection sequence")
             self.ctx.devs.set_zoom(zoom_value, wait=True)
 
             boxes_face: dict[int, tuple[float, float, float, float]] = {}
@@ -106,7 +106,7 @@ class FaceDetectionService:
                 )
 
                 if not model or not model.box:
-                    self.logger.info(f"no box found for angle {angle}")
+                    self.logger.warning(f"no box found for angle {angle}")
                     self._emit_running_progress(angle=angle, boxes_face=boxes_face)
                     continue
 
@@ -122,12 +122,12 @@ class FaceDetectionService:
 
                 if cls_id == 3:
                     boxes_face[angle] = (x1, y1, x2, y2)
-                    self.logger.info(
+                    self.logger.debug(
                         f"accepted box at angle {angle}, cls={cls_id}, box={(x1, y1, x2, y2)}"
                     )
                 elif cls_id == 0:
                     boxes_loop[angle] = (x1, y1, x2, y2)
-                    self.logger.info(
+                    self.logger.debug(
                         f"accepted box at angle {angle}, cls={cls_id}, box={(x1, y1, x2, y2)}"
                     )
                 else:
@@ -136,7 +136,7 @@ class FaceDetectionService:
                 self._emit_running_progress(angle=angle, boxes_face=boxes_face)
 
             if not boxes_face and not boxes_loop:
-                self.logger.info("no boxes found")
+                self.logger.warning("no boxes found")
                 payload = self._emit_empty_result()
                 return FaceDetectionResult(success=True, payload=payload)
 
@@ -145,17 +145,17 @@ class FaceDetectionService:
 
             if boxes_face and face_ratio >= face_min_ratio:
                 boxes = boxes_face
-                self.logger.info(
+                self.logger.debug(
                     f"using loop_face boxes ({len(boxes_face)}/{total_detections}, ratio={face_ratio:.2f})"
                 )
             elif boxes_loop:
                 boxes = boxes_loop
-                self.logger.info(
+                self.logger.debug(
                     f"falling back to loop_all boxes ({len(boxes_loop)}/{total_detections}, ratio={1 - face_ratio:.2f})"
                 )
             else:
                 boxes = boxes_face
-                self.logger.info(f"using loop_face boxes (only source, {len(boxes_face)} entries)")
+                self.logger.debug(f"using loop_face boxes (only source, {len(boxes_face)} entries)")
 
             best_fit_angle_area, area_params = fd.get_flat_face(boxes, start_angle, end_angle, True)
             best_fit_angle_height, height_params = fd.get_flat_face(boxes, start_angle, end_angle, False)
@@ -164,19 +164,19 @@ class FaceDetectionService:
                 "Height": {"angle": best_fit_angle_height, "params": height_params},
             }
 
-            self.logger.info(f"best angle by area: {best_fit_angle_area}")
-            self.logger.info(f"best angle by height: {best_fit_angle_height}")
+            self.logger.debug(f"best angle by area: {best_fit_angle_area}")
+            self.logger.debug(f"best angle by height: {best_fit_angle_height}")
 
             flat_face_angle, best_params, best_name = fd.choose_best_fit(fit_results)
 
-            self.logger.info(f"best params: {best_params}")
-            self.logger.info(f"chosen fit: {best_name}")
+            self.logger.debug(f"best params: {best_params}")
+            self.logger.debug(f"chosen fit: {best_name}")
             self.logger.info(f"best angle: {flat_face_angle}")
 
             self.ctx.devs.aerotech_omega = flat_face_angle
 
             samples_out = fd.get_samples_out(boxes)
-            self.logger.info(f"face detection sequence done, samples: {samples_out}")
+            self.logger.info(f"Face detection sequence complete")
 
             payload = {
                 "running": False,