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			111 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			111 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| # Requirements: numpy, scipy, Pillow,
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| from __future__ import print_function
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| import sys
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| import numpy as np
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| from scipy import ndimage
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| from PIL import Image, ImageFilter, ImageChops
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| import math
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| from os import listdir
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| from os.path import isdir, isfile
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| 
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| roberts_cross_v = np.array([[0, 0, 0],
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|                             [0, 1, 0],
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|                             [0, 0, -1]])
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| 
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| roberts_cross_h = np.array([[0, 0, 0],
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|                             [0, 0, 1],
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|                             [0, -1, 0]])
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| 
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| 
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| def rgb2gray(rgb):
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|     return np.dot(rgb[..., :3], [0.2989, 0.5870, 0.1140])
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| 
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| 
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| 
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| 
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| def save_image(data, outfilename, src_image):
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|     img = Image.fromarray(np.asarray(
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|         np.clip(data, 0, 255), dtype="uint8"), "L")
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|     dest = Image.new("RGBA", (img.width, img.height))
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|     src = img.load()
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|     dst = dest.load()
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| 
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|     realSrc = src_image.load()
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|     mask = src_image.filter(ImageFilter.GaussianBlur(10)).load()
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|     orig = src_image.load()
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| 
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| 
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|     isWire = "wire" in outfilename
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| 
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|     targetR = 104
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|     targetG = 200
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|     targetB = 255
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| 
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|     if isWire:
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|         targetR = 255
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|         targetG = 104
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|         targetB = 232 
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| 
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|     for x in range(img.width):
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|         for y in range(img.height):
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|             realpixl = realSrc[x, y]
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|             greyval = float(src[x, y])
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|             greyval = min(255.0, greyval)
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|             greyval = math.pow(
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|                 min(1, float(greyval / 255.0 * 1)), 1.5) * 255.0 * 1
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|             greyval = max(0, greyval)
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|             alpha = mask[x, y][3] / 255.0 * 1
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| 
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|             edgeFactor = src[x, y] / 255.0
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|             noEdge = 1 - edgeFactor
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| 
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|             shadow = min(1, 1 - realpixl[3] / 255.0 - edgeFactor)
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|             noShadow = 1 - shadow
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| 
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|             dst[x, y] = (
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|                 min(255, int((realpixl[0] / 255.0 * 0.4 + 0.6) * targetR * 1.1)),
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|                 min(255, int((realpixl[1] / 255.0 * 0.4 + 0.6) * targetG * 1.1)),
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|                 min(255, int((realpixl[2] / 255.0 * 0.4 + 0.6) * targetB * 1.1)),
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|                 min(255, int(float(realpixl[3]) * (0.6 + 5 * edgeFactor))))
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| 
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| 
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|     dest.save(outfilename)
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| 
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| 
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| def roberts_cross(infilename, outfilename):
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|     print("Processing", infilename)
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|     img = Image.open(infilename)
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|     img.load()
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|     img = img.filter(ImageFilter.GaussianBlur(0.5))
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| 
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|     image = rgb2gray(np.asarray(img, dtype="int32"))
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|     vertical = ndimage.convolve(image, roberts_cross_v)
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|     horizontal = ndimage.convolve(image, roberts_cross_h)
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|     output_image = np.sqrt(np.square(horizontal) + np.square(vertical))
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|     save_image(output_image, outfilename, img)
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| 
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| 
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| def generateUiPreview(srcPath, buildingId):
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|     print(srcPath, buildingId)
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|     img = Image.open(srcPath)
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|     img.load()
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|     img.thumbnail((110, 110), Image.ANTIALIAS)
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|     img.save("../res/ui/hud/building_previews/" + buildingId + ".png")
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| 
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|     img = img.convert("LA")
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| 
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|     data = img.load()
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|     for x in range(img.width):
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|         for y in range(img.height):
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|             data[x, y] = (data[x, y][0], int(data[x, y][1] * 0.5))
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| 
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|     img.save("../res/ui/hud/building_previews/" + buildingId + "_disabled.png")
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| 
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| 
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| buildings = listdir("buildings")
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| 
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| for buildingId in buildings:
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|     if "hub" in buildingId:
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|         continue
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|     roberts_cross("buildings/" + buildingId + "", "blueprints/" + buildingId + "")
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