You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
97 lines
2.9 KiB
97 lines
2.9 KiB
# Requirements: numpy, scipy, Pillow,
|
|
|
|
import sys
|
|
import numpy as np
|
|
from scipy import ndimage
|
|
from PIL import Image, ImageFilter, ImageChops
|
|
import math
|
|
from os import listdir
|
|
from os.path import isdir, isfile
|
|
|
|
roberts_cross_v = np.array([[0, 0, 0],
|
|
[0, 1, 0],
|
|
[0, 0, -1]])
|
|
|
|
roberts_cross_h = np.array([[0, 0, 0],
|
|
[0, 0, 1],
|
|
[0, -1, 0]])
|
|
|
|
|
|
def rgb2gray(rgb):
|
|
return np.dot(rgb[..., :3], [0.2989, 0.5870, 0.1140])
|
|
|
|
|
|
def save_image(data, outfilename, src_image):
|
|
img = Image.fromarray(np.asarray(
|
|
np.clip(data, 0, 255), dtype="uint8"), "L")
|
|
dest = Image.new("RGBA", (img.width, img.height))
|
|
src = img.load()
|
|
dst = dest.load()
|
|
|
|
realSrc = src_image.load()
|
|
mask = src_image.filter(ImageFilter.GaussianBlur(10)).load()
|
|
orig = src_image.load()
|
|
|
|
for x in range(img.width):
|
|
for y in range(img.height):
|
|
realpixl = realSrc[x, y]
|
|
greyval = float(src[x, y])
|
|
greyval = min(255.0, greyval)
|
|
greyval = math.pow(
|
|
min(1, float(greyval / 255.0 * 1)), 1.5) * 255.0 * 1
|
|
greyval = max(0, greyval)
|
|
alpha = mask[x, y][3] / 255.0 * 1
|
|
|
|
edgeFactor = src[x, y] / 255.0
|
|
noEdge = 1 - edgeFactor
|
|
|
|
shadow = min(1, 1 - realpixl[3] / 255.0 - edgeFactor)
|
|
noShadow = 1 - shadow
|
|
|
|
dst[x, y] = (
|
|
min(255, int((realpixl[0] / 255.0 * 0.4 + 0.6) * 104 * 1.1)),
|
|
min(255, int((realpixl[1] / 255.0 * 0.4 + 0.6) * 200 * 1.1)),
|
|
min(255, int((realpixl[2] / 255.0 * 0.4 + 0.6) * 255 * 1.1)),
|
|
min(255, int(float(realpixl[3]) * (0.6 + 5 * edgeFactor))))
|
|
|
|
|
|
dest.save(outfilename)
|
|
|
|
|
|
def roberts_cross(infilename, outfilename):
|
|
print "Processing", infilename
|
|
img = Image.open(infilename)
|
|
img.load()
|
|
img = img.filter(ImageFilter.GaussianBlur(0.5))
|
|
|
|
image = rgb2gray(np.asarray(img, dtype="int32"))
|
|
vertical = ndimage.convolve(image, roberts_cross_v)
|
|
horizontal = ndimage.convolve(image, roberts_cross_h)
|
|
output_image = np.sqrt(np.square(horizontal) + np.square(vertical))
|
|
save_image(output_image, outfilename, img)
|
|
|
|
|
|
def generateUiPreview(srcPath, buildingId):
|
|
print srcPath, buildingId
|
|
img = Image.open(srcPath)
|
|
img.load()
|
|
img.thumbnail((110, 110), Image.ANTIALIAS)
|
|
img.save("../res/ui/hud/building_previews/" + buildingId + ".png")
|
|
|
|
img = img.convert("LA")
|
|
|
|
data = img.load()
|
|
for x in range(img.width):
|
|
for y in range(img.height):
|
|
data[x, y] = (data[x, y][0], int(data[x, y][1] * 0.5))
|
|
|
|
img.save("../res/ui/hud/building_previews/" + buildingId + "_disabled.png")
|
|
|
|
|
|
buildings = listdir("buildings")
|
|
|
|
for buildingId in buildings:
|
|
if "hub" in buildingId:
|
|
continue
|
|
roberts_cross("buildings/" + buildingId + "", "blueprints/" + buildingId + "")
|