Get new background detect running in simulation mode.

src/openflexure_microscope_server/background_detect.py

@@ -158,23 +158,23 @@ class ColourChannelDetectLUV(BackgroundDetectAlgorithm):
     def background_mask(self, image: np.ndarray) -> np.ndarray:
         """Calculate a binary image, showing whether each pixel is background.
 
+        True is background.
+
         The image should be in LUV format, the output will be binary with the
         same shape in the first two dimensions.
-
-        # human-intuitive way
         """
         d = self.background_data
         if not d:
             raise RuntimeError(
                 "Background is not set: you need to calibrate background detection."
             )
-
+        print(d)
         # Only use the U and V channels of as brightness (L) often changes as the
         # height of the sample changes.
         return np.all(
             np.abs(image[:, :, 1:] - np.array(d.means[1:])[np.newaxis, np.newaxis, :])
             < np.array(d.standard_deviations[1:])[np.newaxis, np.newaxis, :]
-            * self.channel_tolerance,
+            * self.settings.channel_tolerance,
             axis=2,
         )
 
@@ -189,6 +189,9 @@ class ColourChannelDetectLUV(BackgroundDetectAlgorithm):
         """
         image_luv = cv2.cvtColor(image, cv2.COLOR_RGB2LUV)
         mask = self.background_mask(image_luv)
+        print(np.count_nonzero(mask))
+        print(np.prod(mask.shape))
+        print((1 - np.count_nonzero(mask) / np.prod(mask.shape)) * 100)
         return (1 - np.count_nonzero(mask) / np.prod(mask.shape)) * 100
 
     def image_is_sample(self, image: np.ndarray) -> tuple[bool, str]:
@@ -200,7 +203,7 @@ class ColourChannelDetectLUV(BackgroundDetectAlgorithm):
         """
         sample_coverage = self.get_sample_coverage(image)
 
-        is_sample = sample_coverage > self.min_sample_coverage
+        is_sample = sample_coverage > self.settings.min_sample_coverage
         message = f"{sample_coverage}% sample"
         if not is_sample:
             message = "only " + message

src/openflexure_microscope_server/things/camera/__init__.py

@@ -498,7 +498,7 @@ class BaseCamera(lt.Thing):
         return self.active_detector.status
 
     @lt.thing_setting
-    def background_detector_data(self) -> str:
+    def background_detector_data(self) -> dict:
         """The data for each background detector, used to save to disk."""
         data = {}
         for name, obj in self.background_detectors.items():
@@ -511,9 +511,10 @@ class BaseCamera(lt.Thing):
                 "settings": obj.settings.model_dump(),
                 "background_data": bg_data,
             }
+        return data
 
-    @detector_name.setter
-    def detector_name(self, data: str) -> None:
+    @background_detector_data.setter
+    def background_detector_data(self, data: dict) -> None:
         """Set the data for each detector. This should only be called on init.
 
         Do not call over HTTP. Would be good to have a way to make this private.
@@ -548,6 +549,8 @@ class BaseCamera(lt.Thing):
         background = self.grab_jpeg(portal)
         background = np.array(Image.open(background.open()))
         self.active_detector.set_background(background)
+        # Manually save settings as the setter is not called.
+        self.save_settings()
 
 
 CameraDependency = lt.deps.direct_thing_client_dependency(BaseCamera, "/camera/")