123 lines
3.1 KiB
Python
123 lines
3.1 KiB
Python
import numpy as np
|
|
from numpy import random
|
|
from PIL import Image, ImageFilter
|
|
|
|
from ..params import Point
|
|
|
|
|
|
def get_pixel_index(x: int, y: int, width: int) -> int:
|
|
return (y * width) + x
|
|
|
|
|
|
def noise_source_fill_edge(
|
|
source: Image.Image, dims: Point, origin: Point, fill="white", **kw
|
|
) -> Image.Image:
|
|
"""
|
|
Identity transform, source image centered on white canvas.
|
|
"""
|
|
width, height = dims
|
|
|
|
noise = Image.new("RGB", (width, height), fill)
|
|
noise.paste(source, origin)
|
|
|
|
return noise
|
|
|
|
|
|
def noise_source_fill_mask(
|
|
_source: Image.Image, dims: Point, _origin: Point, fill="white", **kw
|
|
) -> Image.Image:
|
|
"""
|
|
Fill the whole canvas, no source or noise.
|
|
"""
|
|
width, height = dims
|
|
|
|
noise = Image.new("RGB", (width, height), fill)
|
|
|
|
return noise
|
|
|
|
|
|
def noise_source_gaussian(
|
|
source: Image.Image, dims: Point, origin: Point, rounds=3, **kw
|
|
) -> Image.Image:
|
|
"""
|
|
Gaussian blur, source image centered on white canvas.
|
|
"""
|
|
noise = noise_source_uniform(source, dims, origin)
|
|
noise.paste(source, origin)
|
|
|
|
for _i in range(rounds):
|
|
noise = noise.filter(ImageFilter.GaussianBlur(5))
|
|
|
|
return noise
|
|
|
|
|
|
def noise_source_uniform(
|
|
_source: Image.Image, dims: Point, _origin: Point, **kw
|
|
) -> Image.Image:
|
|
width, height = dims
|
|
size = width * height
|
|
|
|
noise_r = random.uniform(0, 256, size=size)
|
|
noise_g = random.uniform(0, 256, size=size)
|
|
noise_b = random.uniform(0, 256, size=size)
|
|
|
|
noise = Image.new("RGB", (width, height))
|
|
|
|
for x in range(width):
|
|
for y in range(height):
|
|
i = get_pixel_index(x, y, width)
|
|
noise.putpixel((x, y), (int(noise_r[i]), int(noise_g[i]), int(noise_b[i])))
|
|
|
|
return noise
|
|
|
|
|
|
def noise_source_normal(
|
|
_source: Image.Image, dims: Point, _origin: Point, **kw
|
|
) -> Image.Image:
|
|
width, height = dims
|
|
size = width * height
|
|
|
|
noise_r = random.normal(128, 32, size=size)
|
|
noise_g = random.normal(128, 32, size=size)
|
|
noise_b = random.normal(128, 32, size=size)
|
|
|
|
noise = Image.new("RGB", (width, height))
|
|
|
|
for x in range(width):
|
|
for y in range(height):
|
|
i = get_pixel_index(x, y, width)
|
|
noise.putpixel((x, y), (int(noise_r[i]), int(noise_g[i]), int(noise_b[i])))
|
|
|
|
return noise
|
|
|
|
|
|
def noise_source_histogram(
|
|
source: Image.Image, dims: Point, _origin: Point, **kw
|
|
) -> Image.Image:
|
|
r, g, b = source.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 = get_pixel_index(x, y, width)
|
|
noise.putpixel((x, y), (noise_r[i], noise_g[i], noise_b[i]))
|
|
|
|
return noise
|