kwimage.im_alphablend

Module Contents

Functions

overlay_alpha_layers(layers, keepalpha=True, dtype=np.float32)	Stacks a sequences of layers on top of one another. The first item is the
overlay_alpha_images(img1, img2, keepalpha=True, dtype=np.float32, impl='inplace')	Places img1 on top of img2 respecting alpha channels.
_prep_rgb_alpha(img, dtype=np.float32)
_alpha_blend_simple(rgb1, alpha1, rgb2, alpha2)	Core alpha blending algorithm
_alpha_blend_inplace(rgb1, alpha1, rgb2, alpha2)	Uglier but faster(? maybe not) version of the core alpha blending algorithm
_alpha_blend_numexpr1(rgb1, alpha1, rgb2, alpha2)	Alternative. Not well optimized
_alpha_blend_numexpr2(rgb1, alpha1, rgb2, alpha2)	Alternative. Not well optimized
ensure_alpha_channel(img, alpha=1.0, dtype=np.float32, copy=False)	Returns the input image with 4 channels.

kwimage.im_alphablend.overlay_alpha_layers(layers, keepalpha=True, dtype=np.float32)

Stacks a sequences of layers on top of one another. The first item is the topmost layer and the last item is the bottommost layer.

Parameters

• layers (Sequence[ndarray]) – stack of images

• keepalpha (bool) – if False, the alpha channel is removed after blending

• dtype (np.dtype) – format for blending computation (defaults to float32)

Returns

raster: the blended images

Return type

ndarray

References

http://stackoverflow.com/questions/25182421/overlay-numpy-alpha https://en.wikipedia.org/wiki/Alpha_compositing#Alpha_blending

Example

>>> import kwimage
>>> keys = ['astro', 'carl', 'stars']
>>> layers = [kwimage.grab_test_image(k, dsize=(100, 100)) for k in keys]
>>> layers = [kwimage.ensure_alpha_channel(g, alpha=.5) for g in layers]
>>> stacked = overlay_alpha_layers(layers)
>>> # xdoctest: +REQUIRES(--show)
>>> import kwplot
>>> kwplot.autompl()
>>> kwplot.imshow(stacked)
>>> kwplot.show_if_requested()

kwimage.im_alphablend.overlay_alpha_images(img1, img2, keepalpha=True, dtype=np.float32, impl='inplace')

Places img1 on top of img2 respecting alpha channels. Works like the Photoshop layers with opacity.

Parameters

• img1 (ndarray) – top image to overlay over img2

• img2 (ndarray) – base image to superimpose on

• keepalpha (bool) – if False, the alpha channel is removed after blending

• dtype (np.dtype) – format for blending computation (defaults to float32)

• impl (str, default=inplace) – code specifying the backend implementation

Returns

raster: the blended images

Return type

ndarray

Todo

• [ ] Make fast C++ version of this function

References

http://stackoverflow.com/questions/25182421/overlay-numpy-alpha https://en.wikipedia.org/wiki/Alpha_compositing#Alpha_blending

Example

>>> import kwimage
>>> img1 = kwimage.grab_test_image('astro', dsize=(100, 100))
>>> img2 = kwimage.grab_test_image('carl', dsize=(100, 100))
>>> img1 = kwimage.ensure_alpha_channel(img1, alpha=.5)
>>> img3 = overlay_alpha_images(img1, img2)
>>> # xdoctest: +REQUIRES(--show)
>>> import kwplot
>>> kwplot.autompl()
>>> kwplot.imshow(img3)
>>> kwplot.show_if_requested()

kwimage.im_alphablend._prep_rgb_alpha(img, dtype=np.float32)

kwimage.im_alphablend._alpha_blend_simple(rgb1, alpha1, rgb2, alpha2)

Core alpha blending algorithm

SeeAlso:

_alpha_blend_inplace - alternative implementation

kwimage.im_alphablend._alpha_blend_inplace(rgb1, alpha1, rgb2, alpha2)

Uglier but faster(? maybe not) version of the core alpha blending algorithm using preallocation and in-place computation where possible.

SeeAlso:

_alpha_blend_simple - alternative implementation

Example

>>> rng = np.random.RandomState(0)
>>> rgb1, rgb2 = rng.rand(10, 10, 3), rng.rand(10, 10, 3)
>>> alpha1, alpha2 = rng.rand(10, 10), rng.rand(10, 10)
>>> f1, f2 = _alpha_blend_inplace(rgb1, alpha1, rgb2, alpha2)
>>> s1, s2 = _alpha_blend_simple(rgb1, alpha1, rgb2, alpha2)
>>> assert np.all(f1 == s1) and np.all(f2 == s2)
>>> alpha1, alpha2 = np.zeros((10, 10)), np.zeros((10, 10))
>>> f1, f2 = _alpha_blend_inplace(rgb1, alpha1, rgb2, alpha2)
>>> s1, s2 = _alpha_blend_simple(rgb1, alpha1, rgb2, alpha2)
>>> assert np.all(f1 == s1) and np.all(f2 == s2)

kwimage.im_alphablend._alpha_blend_numexpr1(rgb1, alpha1, rgb2, alpha2)

Alternative. Not well optimized

kwimage.im_alphablend._alpha_blend_numexpr2(rgb1, alpha1, rgb2, alpha2)

Alternative. Not well optimized

kwimage.im_alphablend.ensure_alpha_channel(img, alpha=1.0, dtype=np.float32, copy=False)

Returns the input image with 4 channels.

Parameters

• img (ndarray) – an image with shape [H, W], [H, W, 1], [H, W, 3], or [H, W, 4].

• alpha (float, default=1.0) – default value for missing alpha channel

• dtype (type, default=np.float32) – a numpy floating type

• copy (bool, default=False) – always copy if True, else copy if needed.

Returns

an image with specified dtype with shape [H, W, 4].

Raises

ValueError - if the input image does not have 1, 3, or 4 input channels – or if the image cannot be converted into a float01 representation