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onnx-web/api/onnx_web/image.py

76 lines
2.6 KiB
Python

from numpy import random
from PIL import Image
from typing import Tuple
import numpy as np
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] * blend_imult(mask[0])) + (noise[0] * blend_mult(mask[0]))),
int((source[1] * blend_imult(mask[1])) + (noise[1] * blend_mult(mask[1]))),
int((source[2] * blend_imult(mask[2])) + (noise[2] * blend_mult(mask[2]))),
)
def blend_source_histogram(source_image: Image, dims: Tuple[int, int]) -> Tuple[float, float, float]:
r, g, b = source_image.split()
width, height = dims
size = width * height
hist_r = r.histogram()
hist_g = g.histogram()
hist_b = b.histogram()
noise_r = random.choice(256, p=np.divide(np.copy(hist_r), np.sum(hist_r)), size=size)
noise_g = random.choice(256, p=np.divide(np.copy(hist_g), np.sum(hist_g)), size=size)
noise_b = random.choice(256, p=np.divide(np.copy(hist_b), np.sum(hist_b)), size=size)
noise = Image.new('RGB', (width, height))
for x in range(width):
for y in range(height):
i = x * y
noise.putpixel((x, y), (
noise_r[i],
noise_g[i],
noise_b[i]
))
return noise
# based on https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/master/scripts/outpainting_mk_2.py#L175-L232
def expand_image(source_image: Image, mask_image: Image, dims: Tuple[int, int, int, int], fill = 'white', blend_source=blend_source_histogram, blend_op=blend_mask_inverse_source):
left, right, top, bottom = dims
full_width = left + source_image.width + right
full_height = top + source_image.height + bottom
full_source = Image.new('RGB', (full_width, full_height), fill)
full_source.paste(source_image, (left, top))
full_mask = Image.new('RGB', (full_width, full_height), fill)
full_mask.paste(mask_image, (left, top))
full_noise = blend_source(source_image, (full_width, full_height))
for x in range(full_source.width):
for y in range(full_source.height):
mask_color = full_mask.getpixel((x, y))
noise_color = full_noise.getpixel((x, y))
source_color = full_source.getpixel((x, y))
if mask_color[0] > 0:
full_source.putpixel((x, y), blend_op(source_color, mask_color, noise_color))
return (full_source, full_mask, full_noise, (full_width, full_height))