Add gamma_curve to metadata

src/openflexure_microscope_server/things/camera/__init__.py

@@ -646,7 +646,7 @@ class BaseCamera(lt.Thing):
         """Return camera-specific metadata.
 
         By default, this just adds the subclass name as the camera type.
-        Subclasses can extend by overriding this property and calling `super()`.
+        Subclasses can extend by overriding this property and calling `super().thing_state`.
         """
         return {"camera": self.__class__.__name__}
 

src/openflexure_microscope_server/things/camera/picamera.py

@@ -718,6 +718,11 @@ class StreamingPiCamera2(BaseCamera):
             copy_from=self.default_tuning,
         )
 
+    @lt.property
+    def gamma_correction(self) -> float:
+        """Return the gamma correction from the tuning file."""
+        return tf_utils.get_gamma_curve(self.tuning)
+
     @lt.action
     def set_static_green_equalisation(self, offset: int = 65535) -> None:
         """Set the green equalisation to a static value.
@@ -931,5 +936,6 @@ class StreamingPiCamera2(BaseCamera):
             "exposure_time": self.exposure_time,
             "colour_gains": self.colour_gains,
             "analogue_gain": self.analogue_gain,
+            "gamma_correction": self.gamma_correction,
         }
         return state

src/openflexure_microscope_server/things/camera/picamera_tuning_file_utils.py

@@ -186,6 +186,27 @@ def get_lst(tuning: dict) -> LensShadingModel:
     )
 
 
+def get_gamma_curve(tuning: dict) -> dict[int, float]:
+    """Return the gamma curve from the rpi.contrast section of the tuning file.
+
+    Returns a dictionary mapping input levels to output levels.
+    Defaults to {} if gamma curve is missing.
+    """
+    contrast = find_tuning_algo(tuning, "rpi.contrast")
+    return contrast.get("gamma", {})
+
+
+def set_gamma_curve(tuning: dict, gamma_curve: dict[int, float]) -> dict:
+    """Set the gamma curve in the rpi.contrast section of the tuning file.
+
+    Returns a new tuning dictionary with the updated gamma curve.
+    """
+    output_tuning = deepcopy(tuning)
+    contrast = find_tuning_algo(output_tuning, "rpi.contrast")
+    contrast["gamma"] = {int(k): float(v) for k, v in gamma_curve.items()}
+    return output_tuning
+
+
 def get_colour_gains_from_lst(tuning: dict) -> tuple[float, float]:
     """Get the colour gains that are needed from the lens shading tables.