Image

Read

class image_utils.nodes.image.Read(image_path='', width=100, height=100, channels=4, pixel_type=OpenImageIO.BASETYPE.FLOAT)

Read an existing image

Example:

>>> # import the Read module
>>> from image_utils.nodes import image

>>> # read an EXR image
>>> read_node = image.Read('input.exr')

>>> # pre-multiply it by its alpha
>>> read_node.premult()

>>> # save it as tiff
>>> read_node.write('output.tif')

channels

A tuple of strings containing the names of each color channel

>>> # import the checker module
>>> from image_utils.nodes import image

>>> read_image = image.Read('grid-overscan.exr')
>>> print(read_image.channels)
... ('R', 'G', 'B', 'A')

Return type:tuple Returns:list of existing channel

data_height

Height of the source image’s data window

Return type:int

data_width

Width of the source image’s data window

Return type:int

data_window_coordinate

X and Y coordinate of data window (a.k.a. display window)

>>> # import the checker module
>>> from image_utils.nodes import image

>>> read_image = image.Read('grid-overscan.exr')
>>> print(read_image.data_window_coordinate)
... (-250, -250, 1250, 1250)

Return type:tuple

duplicate(pixel_type=None)

make a exact copy of this image. If a file_format is provided, this will get the specified pixel data type rather than using the same pixel file_format as the source ImageBuf.

Example:

>>> from image_utils.nodes import image
>>> from image_utils.pixel_type import PixelType
>>> # create an image instance
>>> A = image.Read('foo.exr')
>>> # make a copy of it
>>> B = A.duplicate(PixelType().bit8)

Rtype pixel_type:  OpenImageIO.BASETYPE Parameters:pixel_type – new image type. i.e, float, half, 8bit Return type:Image Returns:duplicate of this image

file_format

Returns the file format of the image”

>>> from image_utils.nodes import image
>>> image_node = image.Read('foo.exr')
>>> print(image_node.file_format)
... openexr

Return type:str

has_alpha

Whether or not the image has alpha

Return type:bool Returns:True or False

height

Image height

Return type:int

path

Path to the source image

Return type:str

premult()

pre-multiply the channels by alpha

set_data_window(x1, y1, x2, y2)

set data window (a.k.a. display window)

Parameters:

• x1 (int) – x begin
• y1 (int) – y begin
• x2 (int) – x end
• y2 (int) – y end

unpremult()

un-premultiply the channels by alpha

width

Image width

Return type:int

Constant

Create constant image with specific dimension and color

>>> # import the required module
>>> from image_utils.nodes import image

>>> # create a red 4k by 3k constant image in red
>>> constant_image = image.constant(4000, 3000, (1, 0, 0, 0))

>>> # save it as png
>>> constant_image.write('foo.png')

type width:int param width:image width type height:int param height:image height type color:tuple param color:rgba color type data_type:OpenImageIO.BASETYPE param data_type:  type of image rtype:OpenImageIO.ImageBuf return:constant image

Checker

Create checker image. default is black and white checker color

>>> # import the checker module
>>> from image_utils.nodes import image

>>> # create a 4k checker, red by blue color, with 10 cells
>>> checker_image = image.checker(4000, 4000, (1, 0, 0), (0, 0, 1), 10)
>>> checker_image.write('check_me.png')

Result

type width:int param width:image width type height:int param height:image height type color_a:tuple param color_a:color A type color_b:tuple param color_b:color B type cells:int param cells:number of cell rows type data_type:OpenImageIO.BASETYPE param data_type:  type of image rtype:OpenImageIO.ImageBuf return:checker image