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onnx-web
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per-channel blend

This commit is contained in:
Sean Sube 2023-01-14 16:18:37 -06:00
parent 6fded9de2d
commit 6772cb4297
1 changed files with 11 additions and 6 deletions
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17
api/onnx_web/image.py
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@ -4,14 +4,19 @@ from typing import Tuple
import numpy as np
def blend_mask_inverse_source(source: Tuple[int, int, int], mask: Tuple[int, int, int], noise: int) -> Tuple[int, int, int]:
m = float(noise) / 256
n = 1.0 - m
def blend_mult(a):
return float(a) / 256
def blend_imult(a):
return 1.0 - blend_mult(a)
def blend_mask_inverse_source(source: Tuple[int, int, int], mask: Tuple[int, int, int], noise: Tuple[int, int, int]) -> Tuple[int, int, int]:
return (
int((source[0] * n) + (mask[0] * m)),
int((source[1] * n) + (mask[1] * m)),
int((source[2] * n) + (mask[2] * m)),
int((source[0] * blend_imult(noise[0])) + (mask[0] * blend_mult(noise[0]))),
int((source[1] * blend_imult(noise[1])) + (mask[1] * blend_mult(noise[1]))),
int((source[2] * blend_imult[noise[2]]) + (mask[2] * blend_mult(noise[2]))),
)