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93 lines
3.9 KiB
93 lines
3.9 KiB
import random
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import numpy as np
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from maskedImage import MaskedImage
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class Nnf:
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def __init__(self,input,output,patchSize):
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self.input = input
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self.output = output
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self.patchSize = patchSize
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def randomize(self):
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self.field = np.zeros((self.input.height, self.input.width, 3), dtype=int)
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for x in range(self.input.width):
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for y in range(self.input.height):
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self.field[y,x,0] = random.randint(0,self.output.width)# peut être un -1 sur les random
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self.field[y,x,1] = random.randint(0,self.output.height)
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self.field[y,x,2] = MaskedImage.DSCALE
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self.initialize()
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def initializeFromNnf(self,nnf):
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self.field = np.zeros((self.input.height, self.input.width, 3), dtype=int)
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fx = int(self.input.width/nnf.input.width)
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fy = int(self.input.height/nnf.input.height)
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for y in range(self.input.height):
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for x in range(self.input.width):
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xl = min(int(x/fx),nnf.input.width-1)
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yl = min(int(y/fy),nnf.input.height-1)
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self.field[y,x,0] = nnf.field[yl,xl,0]*fx
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self.field[y,x,1] = nnf.field[yl,xl,1]*fy
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self.field[y,x,2] = MaskedImage.DSCALE
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self.initialize()
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def initialize(self):
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for y in range(self.input.height):
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for x in range(self.input.width):
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self.field[y,x,2] = self.distance(x,y,self.field[y,x,0],self.field[y,x,1])
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iter=0
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maxIter =20
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while (self.field[y,x,2] == MaskedImage.DSCALE and iter<maxIter):
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self.field[y,x,0] = random.randint(0,self.output.width)
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self.field[y,x,1] = random.randint(0,self.output.height)
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self.field[y,x,2] = self.distance(x,y,self.field[y,x,0],self.field[y,x,1])
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iter += 1
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def minimize(self,nbPass):
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for i in range(nbPass):
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for y in range(self.input.height-1):
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for x in range(self.input.width-1):
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if (self.field[y,x,2]>0):
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self.minimizeLink(x,y,1)
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for y in range(self.input.height-1,0,-1):
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for x in range(self.input.width-1,0,-1):
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if (self.field[y,x,2]>0):
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self.minimizeLink(x,y,-1)
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def minimizeLink(self,x,y,direction):
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# horizontale
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if (0<x-direction<self.input.width):
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xp = self.field[y,x-direction,0] +direction
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yp = self.field[y,x-direction,1]
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dp = self.distance(x,y,xp,yp)
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if (dp<self.field[y,x,2]):
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self.field[y,x,0] = xp
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self.field[y,x,1] = yp
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self.field[y,x,2] = dp
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# verticale
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if (0<y-direction<self.input.height):
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xp = self.field[y-direction,x,0]
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yp = self.field[y-direction,x,1] + direction
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dp = self.distance(x,y,xp,yp)
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if (dp<self.field[y,x,2]):
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self.field[y,x,0] = xp
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self.field[y,x,1] = yp
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self.field[y,x,2] = dp
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# recherche random
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zoneRecherche = max(self.output.height,self.output.width)
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while zoneRecherche>0:
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xp = self.field[y,x,0] + random.randint(0,2*zoneRecherche)-zoneRecherche
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xp = self.field[y,x,1] + random.randint(0,2*zoneRecherche)-zoneRecherche
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xp = max(0,min(self.output.width-1,xp))
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yp = max(0,min(self.output.height-1,yp))
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dp = self.distance(x,y,xp,yp)
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if (dp<self.field[y,x,2]):
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self.field[y,x,0] = xp
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self.field[y,x,1] = yp
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self.field[y,x,2] = dp
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zoneRecherche = int(zoneRecherche/2)
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def distance(self,x,y,xp,yp):
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return MaskedImage.distance(self.input,x,y,self.output,xp,yp,self.patchSize)
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