normal-grain-merge 0.0.0

Fused normal and grain merge C extension

normal_grain_merge

This implements a combined version of the blend modes normal and grain merge. Grain merge is performed on s and t with the result normal-merged with b. Subscripts indicate channels, with alpha (α) channels broadcast to three channels.

$$ (((\mathrm{t_{rgb}} + \mathrm{s_{rgb}} - 0.5) * \mathrm{t_\alpha} + \mathrm{t_{rgb}} * (1 - \mathrm{t_\alpha})) * (1 - 0.3) + \mathrm{s_{rgb}} * 0.3) * \mathrm{t_\alpha} + \mathrm{b_{rgb}} * (1 - \mathrm{t_\alpha}) $$

Usage

import numpy as np
from normal_grain_merge import normal_grain_merge, KernelKind


# Example arrays
base = np.zeros((100, 100, 3), dtype=np.uint8)
texture = np.zeros((100, 100, 3), dtype=np.uint8)
skin = np.zeros((100, 100, 4), dtype=np.uint8)
im_alpha = np.zeros((100, 100), dtype=np.uint8)

result_scalar = normal_grain_merge(base, texture, skin, im_alpha, KernelKind.KERNEL_SCALAR.value)
print(result_scalar.shape, result_scalar.dtype)

There are three kernels implemented in this module as defined in KernelKind.

• KERNEL_AUTO: Automatically chooses the kernel, preferring AVX2
• KERNEL_SCALAR: Portable scalar implementation.
• KERNEL_SSE42: SSE4.2 intrinsics kernel. Likely better on AMD CPUs.
• KERNEL_AVX2: AVX2 intrinsics kernel. Likely better on Intel CPUs.

Parameters

All input matrices should have the same height and width.

base

RGB or RGBA, dropping the alpha channel if it exists. The base image for application.

texture

RGB or RGBA, applying the alpha if it exists. This is the texture to be applied.

skin

RGBA, the segmented portion of base to texture. The "skin" of the object the texture is to be applied to.

im_alpha

The alpha of parameter skin. This is mostly a holdover from the Python implementation to deal with NumPy.

kernel

One of KernelKind.