openflexure_microscope_server.background_detect.ColourChannelDetectLUV

class documentation

class ColourChannelDetectLUV(BackgroundDetectAlgorithm): (source)

Constructor: ColourChannelDetectLUV()

Compare images with a known background in LUV colourspace.

This uses an LUV colour space checking only the mean and standard deviation of the U and V channels. The LUV colourspace as it collect colours together in a human- intuitive way.

Method	`background_mask`	Calculate a binary image, showing whether each pixel is background.
Method	`get_sample_coverage`	Return the percentage of the input image that is background.
Method	`image_is_sample`	Label the current image as either background or sample.
Method	`set_background`	Use the input image to update the background distributions.
Instance Variable	`background_data`	The statistics of the background image.

Inherited from BackgroundDetectAlgorithm:

Method	`__init__`	Initialise the algorithm settings.
Method	`background_data.setter`	Set the statistics for the background image.
Method	`settings.setter`	Undocumented
Property	`settings`	The statistics of the background image.
Property	`status`	The status information needed for the GUI. Read only.
Instance Variable	`_background_data`	Undocumented
Instance Variable	`_settings`	Undocumented

def background_mask(self, image: np.ndarray) -> np.ndarray: (source) ¶

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.

def get_sample_coverage(self, image: np.ndarray) -> float: (source) ¶

Return the percentage of the input image that is background.

Evaluate whether it is foreground or background by comparing it to the saved statistics for a background image on a per-pixel basis

Returns
`float`	A value (between 0 and 100) is the percentage of the image that is sample.

def image_is_sample(self, image: np.ndarray) -> tuple[bool, str]: (source) ¶

overrides openflexure_microscope_server.background_detect.BackgroundDetectAlgorithm.image_is_sample

Label the current image as either background or sample.

Returns
`tuple[bool, str]`	A tuple of the result (boolean), and explanation string. The explanation string is formatted so it can be added into a sentence such as `An action was taken because the image is {message}.`

def set_background(self, image: np.ndarray): (source) ¶

overrides openflexure_microscope_server.background_detect.BackgroundDetectAlgorithm.set_background

Use the input image to update the background distributions.

background_data = (source) ¶

overrides openflexure_microscope_server.background_detect.BackgroundDetectAlgorithm.background_data

The statistics of the background image.