axi/examples/layers.py

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2018-03-13 21:47:59 +00:00
# from alpha_shape import alpha_shape
from math import hypot
from PIL import Image
import noise
class Layer(object):
def translate(self, x, y):
return Translate(self, x, y)
def scale(self, x, y):
return Scale(self, x, y)
def power(self, power):
return Power(self, power)
def add(self, other):
return Add(self, other)
def subtract(self, other):
return Subtract(self, other)
def multiply(self, other):
return Multiply(self, other)
def threshold(self, threshold):
return Threshold(self, threshold)
def clamp(self, lo=0, hi=1):
return Clamp(self, lo, hi)
def normalize(self, lo, hi, new_lo, new_hi):
return Normalize(self, lo, hi, new_lo, new_hi)
def filter_points(self, points, lo, hi):
return [(x, y) for x, y in points if lo <= self.get(x, y) < hi]
def alpha_shape(self, points, lo, hi, alpha):
points = self.filter_points(points, lo, hi)
return alpha_shape(points, alpha)
def save(self, path, x1, y1, x2, y2, scale=1, lo=0, hi=1):
w = int(round((x2 - x1) * scale))
h = int(round((y2 - y1) * scale))
data = bytearray(w * h)
for y in range(h):
for x in range(w):
sx = x1 + (x2 - x1) * x / (w - 1)
sy = y1 + (y2 - y1) * y / (h - 1)
v = (self.get(sx, sy) - lo) / (hi - lo)
v = max(0, min(255, int(v * 255)))
data[y*w+x] = v
# for y in range(y1, y2):
# for x in range(x1, x2):
# v = (self.get(x, y) - lo) / (hi - lo)
# v = max(0, min(255, int(v * 255)))
# data[y*w+x] = v
im = Image.frombytes('L', (w, h), bytes(data))
im.save(path, 'png')
class Constant(Layer):
def __init__(self, value):
self.value = value
def get(self, x, y):
return self.value
class Noise(Layer):
def __init__(self, octaves=1):
self.octaves = octaves
def get(self, x, y):
return noise.snoise2(x, y, self.octaves)
class Translate(Layer):
def __init__(self, layer, x, y):
self.layer = layer
self.x = x
self.y = y
def get(self, x, y):
return self.layer.get(self.x + x, self.y + y)
class Scale(Layer):
def __init__(self, layer, x, y):
self.layer = layer
self.x = x
self.y = y
def get(self, x, y):
return self.layer.get(self.x * x, self.y * y)
class Power(Layer):
def __init__(self, layer, power):
self.layer = layer
self.power = power
def get(self, x, y):
return self.layer.get(x, y) ** self.power
class Add(Layer):
def __init__(self, a, b):
self.a = a
self.b = b
def get(self, x, y):
return self.a.get(x, y) + self.b.get(x, y)
class Subtract(Layer):
def __init__(self, a, b):
self.a = a
self.b = b
def get(self, x, y):
return self.a.get(x, y) - self.b.get(x, y)
class Multiply(Layer):
def __init__(self, a, b):
self.a = a
self.b = b
def get(self, x, y):
return self.a.get(x, y) * self.b.get(x, y)
class Threshold(Layer):
def __init__(self, layer, threshold):
self.layer = layer
self.threshold = threshold
def get(self, x, y):
return 0 if self.layer.get(x, y) < self.threshold else 1
class Clamp(Layer):
def __init__(self, layer, lo=0, hi=1):
self.layer = layer
self.lo = lo
self.hi = hi
def get(self, x, y):
v = self.layer.get(x, y)
v = min(v, self.hi)
v = max(v, self.lo)
return v
class Normalize(Layer):
def __init__(self, layer, lo, hi, new_lo, new_hi):
self.layer = layer
self.lo = lo
self.hi = hi
self.new_lo = new_lo
self.new_hi = new_hi
def get(self, x, y):
v = self.layer.get(x, y)
p = (v - self.lo) / (self.hi - self.lo)
v = self.new_lo + p * (self.new_hi - self.new_lo)
return v
class Distance(Layer):
def __init__(self, x, y, maximum, gamma=1):
self.x = x
self.y = y
self.maximum = maximum
self.gamma = gamma
def get(self, x, y):
return (hypot(x - self.x, y - self.y) / self.maximum) ** self.gamma