stable-diffusion-mat-outpainting-primer / datasets /mask_generator_512_small.py
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import numpy as np
from PIL import Image, ImageDraw
import math
import random
def RandomBrush(
max_tries,
s,
min_num_vertex = 4,
max_num_vertex = 18,
mean_angle = 2*math.pi / 5,
angle_range = 2*math.pi / 15,
min_width = 12,
max_width = 48):
H, W = s, s
average_radius = math.sqrt(H*H+W*W) / 8
mask = Image.new('L', (W, H), 0)
for _ in range(np.random.randint(max_tries)):
num_vertex = np.random.randint(min_num_vertex, max_num_vertex)
angle_min = mean_angle - np.random.uniform(0, angle_range)
angle_max = mean_angle + np.random.uniform(0, angle_range)
angles = []
vertex = []
for i in range(num_vertex):
if i % 2 == 0:
angles.append(2*math.pi - np.random.uniform(angle_min, angle_max))
else:
angles.append(np.random.uniform(angle_min, angle_max))
h, w = mask.size
vertex.append((int(np.random.randint(0, w)), int(np.random.randint(0, h))))
for i in range(num_vertex):
r = np.clip(
np.random.normal(loc=average_radius, scale=average_radius//2),
0, 2*average_radius)
new_x = np.clip(vertex[-1][0] + r * math.cos(angles[i]), 0, w)
new_y = np.clip(vertex[-1][1] + r * math.sin(angles[i]), 0, h)
vertex.append((int(new_x), int(new_y)))
draw = ImageDraw.Draw(mask)
width = int(np.random.uniform(min_width, max_width))
draw.line(vertex, fill=1, width=width)
for v in vertex:
draw.ellipse((v[0] - width//2,
v[1] - width//2,
v[0] + width//2,
v[1] + width//2),
fill=1)
if np.random.random() > 0.5:
mask.transpose(Image.FLIP_LEFT_RIGHT)
if np.random.random() > 0.5:
mask.transpose(Image.FLIP_TOP_BOTTOM)
mask = np.asarray(mask, np.uint8)
if np.random.random() > 0.5:
mask = np.flip(mask, 0)
if np.random.random() > 0.5:
mask = np.flip(mask, 1)
return mask
def RandomMask(s, hole_range=[0,1]):
coef = min(hole_range[0] + hole_range[1], 1.0)
while True:
mask = np.ones((s, s), np.uint8)
def Fill(max_size):
w, h = np.random.randint(max_size), np.random.randint(max_size)
ww, hh = w // 2, h // 2
x, y = np.random.randint(-ww, s - w + ww), np.random.randint(-hh, s - h + hh)
mask[max(y, 0): min(y + h, s), max(x, 0): min(x + w, s)] = 0
def MultiFill(max_tries, max_size):
for _ in range(np.random.randint(max_tries)):
Fill(max_size)
MultiFill(int(3 * coef), s // 2)
MultiFill(int(2 * coef), s)
mask = np.logical_and(mask, 1 - RandomBrush(int(4 * coef), s)) # hole denoted as 0, reserved as 1
hole_ratio = 1 - np.mean(mask)
if hole_range is not None and (hole_ratio <= hole_range[0] or hole_ratio >= hole_range[1]):
continue
return mask[np.newaxis, ...].astype(np.float32)
def BatchRandomMask(batch_size, s, hole_range=[0, 1]):
return np.stack([RandomMask(s, hole_range=hole_range) for _ in range(batch_size)], axis=0)
if __name__ == '__main__':
res = 512
# res = 256
cnt = 2000
tot = 0
for i in range(cnt):
mask = RandomMask(s=res)
tot += mask.mean()
print(tot / cnt)