isimple.maths package

Submodules

isimple.maths.colors module

class isimple.maths.colors.Color(*args, **kwargs)

Bases: isimple.core.config.BaseConfig

np3d

list

convert(colorspace: str) → tuple

classmethod from_str(color: str) → isimple.maths.colors.Color

classmethod normalize_channel(v)

class isimple.maths.colors.HsvColor(*args, **kwargs)

Bases: isimple.maths.colors.Color

classmethod hue_wraps(v)

class isimple.maths.colors.RgbColor(*args, **kwargs)

Bases: isimple.maths.colors.Color

class isimple.maths.colors.BgrColor(*args, **kwargs)

Bases: isimple.maths.colors.Color

isimple.maths.colors.convert(color: isimple.maths.colors.Color, to: Type[isimple.maths.colors.Color]) → isimple.maths.colors.Color

isimple.maths.colors.as_hsv(color: isimple.maths.colors.Color) → isimple.maths.colors.HsvColor

isimple.maths.colors.as_bgr(color: isimple.maths.colors.Color) → isimple.maths.colors.BgrColor

isimple.maths.colors.as_rgb(color: isimple.maths.colors.Color) → isimple.maths.colors.RgbColor

isimple.maths.colors.complementary(color: isimple.maths.colors.Color) → isimple.maths.colors.Color

isimple.maths.colors.css_hex(color: isimple.maths.colors.Color) → str

isimple.maths.coordinates module

class isimple.maths.coordinates.Coo

Bases: isimple.core.config.BaseConfig

Image coordinate

rel

list

class isimple.maths.coordinates.ShapeCoo

Bases: isimple.maths.coordinates.Coo

abs

idx

cv2

value(image: numpy.ndarray) → Any

transform(matrix: numpy.ndarray, shape: Tuple[int, int])

class isimple.maths.coordinates.Roi

Bases: isimple.core.config.BaseConfig

Region of interest

isimple.maths.images module

isimple.maths.images.ckernel(size: int) → numpy.ndarray

Circular filter kernel

isimple.maths.images.overlay(frame: numpy.ndarray, overlay: numpy.ndarray, alpha: float = 0.5) → numpy.ndarray

Overlay frame image with overlay image. * Both images should be in the BGR color space

isimple.maths.images.crop_mask(mask: numpy.ndarray) → Tuple[numpy.ndarray, numpy.ndarray, Tuple[int, int]]

Crop a binary mask image array to its minimal (rectangular) size to exclude unnecessary regions

isimple.maths.images.rect_contains(rect: numpy.ndarray, point: isimple.maths.coordinates.ShapeCoo) → bool

Check whether point is in rect :param rect: an ‘array rectangle’: [first_row, last_row, first_column, last_column] :param point: a coordinate as (row, column) :return:

isimple.maths.images.mask(image: numpy.ndarray, mask: numpy.ndarray, rect: numpy.ndarray)

isimple.maths.images.area_pixelsum(image)

Calculate area in px^2 by summing pixels

Parameters:image – Binary input image (numpy array). Should already be masked and filtered. Returns:Area as # of pixels

isimple.maths.images.to_mask(image: numpy.ndarray, kernel: numpy.ndarray = array([[ 0, 0, 0, 255, 0, 0, 0], [ 0, 255, 255, 255, 255, 255, 0], [ 0, 255, 255, 255, 255, 255, 0], [255, 255, 255, 255, 255, 255, 255], [ 0, 255, 255, 255, 255, 255, 0], [ 0, 255, 255, 255, 255, 255, 0], [ 0, 0, 0, 255, 0, 0, 0]], dtype=uint8)) → numpy.ndarray

Convert a .png image to a binary mask

Module contents