Python PNMImage.fill方法代码示例

# 需要导入模块: from pandac.PandaModules import PNMImage [as 别名]
# 或者: from pandac.PandaModules.PNMImage import fill [as 别名]
    def _createMapTextureCard(self):
        mapImage = PNMImage(MAP_RESOLUTION, MAP_RESOLUTION)
        mapImage.fill(*self._bgColor)
        fgColor = VBase4D(*self._fgColor)
        for x in xrange(self._mazeHeight):
            for y in xrange(self._mazeWidth):
                if self._mazeCollTable[y][x] == 1:
                    ax = float(x) / self._mazeWidth * MAP_RESOLUTION
                    invertedY = self._mazeHeight - 1 - y
                    ay = float(invertedY) / self._mazeHeight * MAP_RESOLUTION
                    self._drawSquare(mapImage, int(ax), int(ay), 10, fgColor)

        mapTexture = Texture('mapTexture')
        mapTexture.setupTexture(Texture.TT2dTexture, self._maskResolution, self._maskResolution, 1, Texture.TUnsignedByte, Texture.FRgba)
        mapTexture.setMinfilter(Texture.FTLinear)
        mapTexture.load(mapImage)
        mapTexture.setWrapU(Texture.WMClamp)
        mapTexture.setWrapV(Texture.WMClamp)
        mapImage.clear()
        del mapImage
        cm = CardMaker('map_cardMaker')
        cm.setFrame(-1.0, 1.0, -1.0, 1.0)
        map = self.attachNewNode(cm.generate())
        map.setTexture(mapTexture, 1)
        return map

# 需要导入模块: from pandac.PandaModules import PNMImage [as 别名]
# 或者: from pandac.PandaModules.PNMImage import fill [as 别名]
def getWaterSurface(manager, polycount=50000, size=(512, 512)):
    # Get cache directory...
    cacheDir = manager.get("paths").getConfig().find("cache").get("path")

    # Check if the data required already exists...
    cachedWaterSurface = "%s/plane-%dx%d-%dk.bam" % (cacheDir, size[0], size[1], int(polycount / 1000))
    try:
        return loader.loadModel(cachedWaterSurface)
    except:
        pass

    # Make cache directory if needed...
    if not os.path.isdir(cacheDir):
        os.mkdir(cacheDir)

    # Put in an image...
    img = PNMImage(*size)
    img.makeGrayscale()
    img.fill(0, 0, 0)
    img.write("%s/black-%dx%d.png" % (cacheDir, size[0], size[1]))

    # Put in a mesh...
    ht = HeightfieldTesselator("plane")
    assert ht.setHeightfield(Filename("%s/black-%dx%d.png" % (cacheDir, size[0], size[1])))
    ht.setPolyCount(polycount)
    ht.setFocalPoint(size[0] * 0.5, size[1] * 0.5)
    node = ht.generate()
    node.setPos(-0.5 * size[0], 0.5 * size[1], 0)
    node.flattenLight()
    node.writeBamFile(cachedWaterSurface)

    return node

# 需要导入模块: from pandac.PandaModules import PNMImage [as 别名]
# 或者: from pandac.PandaModules.PNMImage import fill [as 别名]
	def run(self):
		size = 256
		pb = Perlin.Perlin( persistance = 0.500, smooth = False, seed = random.random() )
		myImage2 = pb.imgNoise2D(size,True)
		
		myImage=PNMImage(size,size)
		myImage.makeGrayscale()
		myImage.setMaxval( (2<<16)-1 )
		myImage.fill(0.5)
		line = lineDrawer.LineDrawer(myImage,(42,180),(13,253),13)
		
		for x in range(size):
			for y in range(size):
				gray = myImage.getGray(x,y) - 0.5
				gray = gray + (myImage2.getGray(x,y) - 0.5)
				myImage.setGray(x,y,gray + 0.5)
		

		self.myTexture.load(myImage)

# 需要导入模块: from pandac.PandaModules import PNMImage [as 别名]
# 或者: from pandac.PandaModules.PNMImage import fill [as 别名]
	def imgNoise2D(self, size = 512, autoOctave = False):
		myImage=PNMImage(1,1)
		myImage.makeGrayscale()
		myImage.setMaxval( (2<<16)-1 )
		myImage.fill(0.5)
		
		octaves = self.numberOfOctaves
		if autoOctave == True:
			octaves = int(math.log(size,2))
			self.pNoise = range(0,octaves)
			random.seed(self.seed)
			for i in range(1,octaves):
				self.pNoise[i] = PerlinNoise2( 1, 1, 256, random.randint(1,10000))
		
		for o in range(1,octaves):
			
			freq = 2**o
			oldImage = myImage
			myImage = PNMImage(freq+1,freq+1)
			myImage.makeGrayscale()
			myImage.setMaxval( (2<<16)-1 )
			myImage.gaussianFilterFrom(1.0, oldImage)
			
			for x in range(0,freq):
				for y in range(0,freq):
					newNoise = (self.pNoise[o].noise( x, y)*(self.persistance**o)) / 2
					myImage.setGray(x,y, myImage.getGray(x,y) + newNoise)#*32)
			for i in range(0,freq+1):
				myImage.setGray(i,freq, myImage.getGray(i%freq,0))
				myImage.setGray(freq,i, myImage.getGray(0,i%freq))
		
		oldImage = myImage
		myImage = PNMImage(size,size)
		myImage.makeGrayscale()
		myImage.setMaxval( (2<<16)-1 )
		myImage.gaussianFilterFrom(1.0, oldImage)
		
		return myImage

# 需要导入模块: from pandac.PandaModules import PNMImage [as 别名]
# 或者: from pandac.PandaModules.PNMImage import fill [as 别名]
	def flattenArea( self ):
		tilePos = (500,500)
		tileSize = (4000,4000)
		
		imgTilePos = self.world2MapPos(tilePos)
		imgTileSize = self.world2MapPos( (tilePos[0] + tileSize[0], tilePos[1] + tileSize[1]) )
		imgTileSize = (imgTileSize[0] - imgTilePos[0], imgTileSize[1] - imgTilePos[1])
		
		tileSquare = PNMImage(Filename("tile.png"))
		
		tileStamp = PNMImage(int(imgTileSize[0] * (5/3)),int(imgTileSize[1] * (5/3)))
		tileStamp.makeGrayscale()
		tileStamp.addAlpha()
		
		tileStamp.gaussianFilterFrom(1, tileSquare)
		
		count = 4
		total = 0.0
		
		selectXLow = int(imgTilePos[0] + imgTileSize[0] * 0.25)
		selectXHigh = int(imgTilePos[0] + imgTileSize[0] * 0.75)
		selectYLow = int(imgTilePos[1] + imgTileSize[1] * 0.25)
		selectYHigh = int(imgTilePos[1] + imgTileSize[1] * 0.75)
		
		total += self.myImage.getGray(selectXLow,selectYLow)
		total += self.myImage.getGray(selectXLow,selectYLow)
		total += self.myImage.getGray(selectXHigh,selectYHigh)
		total += self.myImage.getGray(selectXHigh,selectYHigh)
		average = total/count
		
		tileStamp.fill(average)
		
		edgeWidth = imgTilePos[0]*(1/3)
		
		self.myImage.blendSubImage(tileStamp, int( imgTilePos[0]-edgeWidth), 
											  int( imgTilePos[1]-edgeWidth), 
										0, 0, int(imgTileSize[0]*( 5/3 )  ), 
											  int(imgTileSize[1]*( 5/3 )  ), 1)

# 需要导入模块: from pandac.PandaModules import PNMImage [as 别名]
# 或者: from pandac.PandaModules.PNMImage import fill [as 别名]
class PerlinTest(DirectObject):
    def __init__(self):
        self.size = 64
        self.p = Perlin.Perlin(numberOfOctaves=10, persistance=0.75, smooth=False)
        self.myImage = PNMImage(self.size, self.size)
        self.myImage.makeGrayscale()
        self.myTexture = Texture()
        self.myImage.fill(0.5)
        self.myTexture.load(self.myImage)
        self.imageObject = OnscreenImage(image=self.myTexture, pos=(0, 0, 0))
        self.myList = [None] * (self.size)
        for a in range(self.size):
            self.myList[a] = [0.5] * (self.size)
        taskMgr.add(self.noiseTaskVerySmart, "perlinNoiseTask")
        self.startTime = time()
        self.noiseTaskVerySmart()
        self.accept("arrow_up", self.run)
        self.i = [None] * (self.size + 1)
        for x in range(0, self.size + 1):
            self.i[x] = [None] * (self.size + 1)

    def run(self):
        for a in range(self.size):
            self.myList[a] = [0.5] * (self.size)
        self.startTime = time()
        taskMgr.add(self.noiseTaskVerySmart, "perlinNoiseTask")

    def noiseTask(self, Task=None):
        numLines = 8
        if Task == None:
            y = 0
        else:
            y = Task.frame * numLines

        for yNum in range(0, numLines):
            for x in range(0, self.size):
                i = self.p.noise2D(float(x) / self.size, float(y + yNum) / self.size)
                self.myImage.setGray(x, y + yNum, (i + 1.0) / 2)

        self.myTexture.load(self.myImage)
        if Task != None:
            if self.size >= y + numLines:
                return Task.cont
            else:
                self.myTexture.load(self.myImage)
                print time() - self.startTime
                return Task.done

    def noiseTaskSmart(self, Task=None):
        if Task == None:
            o = 0
        else:
            o = Task.frame
        p = Perlin.Perlin(numberOfOctaves=1, smooth=False, seed=0)
        freq = 2 ** o
        for x in range(0, freq + 1):
            for y in range(0, freq + 1):
                self.i[x][y] = p.intNoise2D(x * freq, y * freq)

        for y in range(0, self.size):
            for x in range(0, self.size):
                intX = (x * freq) / self.size
                fraX = (float(x) * freq) / self.size - intX
                intY = (y * freq) / self.size
                i1 = p.linearInterpolate(self.i[intX][intY], self.i[intX + 1][intY], fraX)
                i2 = p.linearInterpolate(self.i[intX][intY + 1], self.i[intX + 1][intY + 1], fraX)
                interNoise = p.linearInterpolate(i1, i2, (float(y) * freq) / self.size - intY)
                self.myList[x][y] += interNoise * (0.75 ** o) / 2
                self.myImage.setGray(x, y, self.myList[x][y])

        self.myTexture.load(self.myImage)
        if Task != None:
            if freq < self.size:
                return Task.cont
            else:
                print time() - self.startTime
                return Task.done

    def noiseTaskVerySmart(self, Task=None):
        if Task == None:
            o = 0
        else:
            o = Task.frame
        p = Perlin.Perlin(numberOfOctaves=1, smooth=False, seed=0)
        freq = 2 ** o
        self.oldImage = self.myImage
        self.myImage = PNMImage(freq + 1, freq + 1)
        self.myImage.makeGrayscale()
        self.myImage.gaussianFilterFrom(1.0, self.oldImage)

        for x in range(0, freq + 1):
            for y in range(0, freq + 1):
                self.myImage.setGray(
                    x, y, self.myImage.getGray(x, y) + p.intNoise2D(x * freq, y * freq) * (0.75 ** o) / 2
                )

        self.myTexture.load(self.myImage)
        if Task != None:
            if freq < self.size:
                return Task.cont
#.........这里部分代码省略.........