imagecat.operator.util module¶

Functions that produce, consume, and modify Imagecat images.

imagecat.operator.util.array(ndim=None, shape=None, dtype=None)[source]¶

Factory for parameter converters that return arrays.

Parameters

ndim (integer, optional) – Raise exceptions if the number of value dimensions don’t match.
shape (integer or tuple of integers, optional) – Raise exceptions if the value shape doesn’t match.
dtype (numpy.dtype, optional) – If specified, the returned array will be coerced to the given dtype.

Returns

converter – Callable that takes a single value as input and produces a numpy.ndarray as output.

Return type

callable

imagecat.operator.util.log_result(log, name, operation, output, **parameters)[source]¶: Standard logging output for operators when they’re executed.

imagecat.operator.util.optional_image(name, inputs, input)[source]¶

Extract an optional image from task inputs.

Parameters

name (hashable object, required) – The name of the task being executed.
inputs (Named Inputs, required) – Named inputs containing task function arguments.
input (hashable object, required) – Name of the optional input image.

Raises

RuntimeError – If inputs contains input, but it isn’t a imagecat.data.Image.

Returns

image – The optional image from inputs.

Return type

class:imagecat.data.Image or None

imagecat.operator.util.optional_input(name, inputs, input, *, type=None, default=None)[source]¶

Extract an optional parameter from task inputs.

Parameters

name (hashable object, required) – The name of the task being executed.
inputs (Named Inputs, required) – Named inputs containing task function arguments.
input (hashable object, required) – Name of the input parameter.
type (callable, optional) – Function for testing / converting the parameter value.
default (Any python object, optional) – Default value that will be returned if inputs doesn’t contain input.

Returns

parameter – The optional parameter from inputs, or the default value.

Return type

Any python object.

imagecat.operator.util.optional_layer(name, inputs, input, *, layer=None, role=None, depth=None, dtype=None)[source]¶

Extract an optional layer from task inputs.

Parameters

name (hashable object, required) – The name of the task being executed.
inputs (Named Inputs, required) – Named inputs containing task function arguments.
input (hashable object, required) – Name of the optional input image.
layer (str, optional) – The name of the optional layer. If None (the default) and the image only contains one layer, use it.
role (imagecat.data.Role, optional) – If specified, the layer must have a matching role.
depth (int, optional) – If specified, the layer must have a matching depth (number of channels).
dtype (numpy.dtype, optional) – If specified, the layer must have a matching dtype.

Returns

layername (str or None) – The name of the matching layer.
layer (imagecat.data.Layer or None) – The matching layer.

imagecat.operator.util.require_image(name, inputs, input)[source]¶

Extract an image from task inputs.

Parameters

name (hashable object, required) – The name of the task being executed.
inputs (Named Inputs, required) – Named inputs containing task function arguments.
input (hashable object, required) – Name of the required input image.

Raises

RuntimeError – If inputs doesn’t contain the required input.

Returns

image – The required image from inputs.

Return type

class:imagecat.data.Image

imagecat.operator.util.require_input(name, inputs, input, *, type=None)[source]¶

Extract a parameter from task inputs.

Parameters

name (hashable object, required) – The name of the task being executed.
inputs (Named Inputs, required) – Named inputs containing task function arguments.
input (hashable object, required) – Name of the required input parameter.
type (callable, optional) – Function for testing / converting the type of the input parameter value.

Raises

RuntimeError – If inputs doesn’t contain the required input.

Returns

parameter – The required parameter from inputs.

Return type

Any python object.

imagecat.operator.util.require_layer(name, inputs, input, *, layer=None, role=None, depth=None, dtype=None)[source]¶

Extract a layer from task inputs.

Parameters

name (hashable object, required) – The name of the task being executed.
inputs (Named Inputs, required) – Named inputs containing task function arguments.
input (hashable object, required) – Name of the required input image.
layer (str, optional) – The name of the required layer. If None (the default) and the image only contains one layer, use it.
role (imagecat.data.Role, optional) – If specified, the layer must have a matching role.
depth (int, optional) – If specified, the layer must have a matching depth (number of channels).
dtype (numpy.dtype, optional) – If specified, the layer must have a matching dtype.

Raises

RuntimeError – If a layer matching all of the criteria can’t be found.

Returns

layername (str) – The name of the matching layer.
layer (imagecat.data.Layer) – The matching layer.

imagecat.operator.util.transform(source, target_shape, *, pivot, position, orientation, scale, order)[source]¶

Transform an image using an affine transformation.

Parameters

source (numpy.ndarray, required) – Image to be transformed.
target_shape (2-tuple of integers, required) – Desired output image size, as a (rows, cols) tuple. Note that this does not have to match the size of the source image. By default, the source image will be centered in the output, cropped if necessary.
pivot (2-tuple of numbers, required) – Location of the point on the source image around which scaling and rotation takes place.
orientation (number, required) – Rotation of the source around its pivot point, in degrees. Positive angles lead to counter-clockwise rotation.
position (2-tuple of numbers, required) – Position of the image pivot point relative to target_shape.
scale (2-tuple of numbers, required) – Scale of the source image around its pivot point.

Returns

rowoffset (integer) – Vertical offset of the returned array relative to the upper-left corner of target_shape
coloffset (integer) – Horizontal offset of the returned array relative to the upper-left corner of target_shape
image (numpy.ndarray) – The transformed image.