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Add unit tests for ChannelDeviationLUV background detector

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This commit is contained in:
Julian Stirling 2025-11-25 17:01:45 +00:00
parent e5d2ebbb79
commit 2749a1818c
2 changed files with 148 additions and 6 deletions
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14
src/openflexure_microscope_server/background_detect.py
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@ -207,11 +207,6 @@ class ColourChannelDetectLUV(BackgroundDetectAlgorithm):
The image should be in LUV format, the output will be binary with the
same shape in the first two dimensions.
"""
if not self.background_data:
raise MissingBackgroundDataError(
"Background is not set: you need to calibrate background detection."
)
# The ``[1:]`` selects only the U and V channels of the image.
# Only U and V are used as brightness (L) often changes as
# the height of the sample changes.
@ -236,6 +231,10 @@ class ColourChannelDetectLUV(BackgroundDetectAlgorithm):
:returns: A value (between 0 and 100) is the percentage of the image that is
sample.
"""
if not self.background_data:
raise MissingBackgroundDataError(
"Background is not set: you need to calibrate background detection."
)
image_luv = cv2.cvtColor(image, cv2.COLOR_RGB2LUV)
mask = self.background_mask(image_luv)
@ -302,6 +301,10 @@ class ChannelDeviationLUV(BackgroundDetectAlgorithm):
:returns: A value (between 0 and 100) is the percentage of the image that is
sample.
"""
if not self.background_data:
raise MissingBackgroundDataError(
"Background is not set: you need to calibrate background detection."
)
image_luv = cv2.cvtColor(image, cv2.COLOR_RGB2LUV)
stds = _chunked_stds(image_luv, 8, 8)
@ -335,7 +338,6 @@ class ChannelDeviationLUV(BackgroundDetectAlgorithm):
def set_background(self, image: np.ndarray) -> None:
"""Use the input image to update the background distributions."""
image_luv = cv2.cvtColor(image, cv2.COLOR_RGB2LUV)
mu = np.zeros(3)
c_stds = _chunked_stds(image_luv, 8, 8)
channel_blank = np.all(c_stds == 0, axis=(0, 1))