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from __future__ import print_function
import vigra
import vigra.graphs as vigraph
import pylab
import numpy
np=numpy
import sys
import matplotlib
import pylab as plt
import math
from matplotlib.widgets import Slider, Button, RadioButtons
def makeWeights(gamma):
global hessian,gradmag,gridGraph
print("hessian",hessian.min(),hessian.max())
print("raw ",raw.min(),raw.max())
wImg= numpy.exp((gradmag**0.5)*gamma*-1.0)#**0.5
wImg = numpy.array(wImg).astype(numpy.float32)
w=vigra.graphs.implicitMeanEdgeMap(gridGraph,wImg)
return w
def makeVisuImage(path,img):
coords = (path[:,0],path[:,1])
visuimg =img.copy()
iR=visuimg[:,:,0]
iG=visuimg[:,:,1]
iB=visuimg[:,:,2]
iR[coords]=255
iG[coords]=0
iB[coords]=0
visuimg-=visuimg.min()
visuimg/=visuimg.max()
return visuimg
f = '100075.jpg'
f = '69015.jpg'
#f = "/media/tbeier/GSP1RMCPRFR/iso.03530.png"
img = vigra.impex.readImage(f)
print(img.shape)
if(img.shape[2]==1):
img = numpy.concatenate([img]*3,axis=2)
imgLab = img
imgLab = vigra.taggedView(imgLab,'xyc')
else:
imgLab = vigra.colors.transform_RGB2Lab(img)
sigma = 1.0
imgLab-=imgLab.min()
imgLab/=imgLab.max()
imgLab*=255
img-=img.min()
img/=img.max()
img*=255
print(imgLab.shape)
print("interpolate image")
imgLabSmall = imgLab
# make a few edge weights
gradmag = numpy.squeeze(vigra.filters.gaussianGradientMagnitude(imgLabSmall,sigma))
hessian = numpy.squeeze(vigra.filters.hessianOfGaussianEigenvalues(imgLabSmall[:,:,0],sigma))[:,:,0]
hessian-=hessian.min()
raw = 256-imgLabSmall[:,:,0].copy()
gridGraph = vigraph.gridGraph(imgLab.shape[:2],False)
weights = makeWeights(3.0)
pathFinder = vigraph.ShortestPathPathDijkstra(gridGraph)
visuimg =img.copy()
ax = plt.gca()
fig = plt.gcf()
visuimg-=visuimg.min()
visuimg/=visuimg.max()
implot = ax.imshow(numpy.swapaxes(visuimg,0,1),cmap='gray')
clickList=[]
frozen = False
axslider = plt.axes([0.0, 0.00, 0.4, 0.075])
axfreeze = plt.axes([0.6, 0.00, 0.1, 0.075])
axunfreeze = plt.axes([0.8, 0.00, 0.1, 0.075])
bfreeze = Button(axfreeze, 'freeze')
bunfreeze = Button(axunfreeze, 'unfrease and clear')
sgamma = Slider(axslider, 'gamma', 0.01, 5.0, valinit=1.0)
def onclick(event):
global clickList
global weights
global img
if event.xdata != None and event.ydata != None:
xRaw,yRaw = event.xdata,event.ydata
if not frozen and xRaw >=0.0 and yRaw>=0.0 and xRaw<img.shape[0] and yRaw<img.shape[1]:
x,y = int(math.floor(event.xdata)),int(math.floor(event.ydata))
clickList.append((x,y))
if len(clickList)==2:
source = gridGraph.coordinateToNode(clickList[0])
target = gridGraph.coordinateToNode(clickList[1])
weights = makeWeights(sgamma.val)
#path = pathFinder.run(weights, source,target).path(pathType='coordinates')
path = pathFinder.run(weights, source).path(pathType='coordinates',target=target)
visuimg = makeVisuImage(path,img)
implot.set_data(numpy.swapaxes(visuimg,0,1))
plt.draw()
def freeze(event):
global frozen
frozen=True
def unfreeze(event):
global frozen,clickList
frozen=False
clickList = []
def onslide(event):
global img,gradmag,weights,clickList,sgamma
weights = makeWeights(sgamma.val)
print("onslide",clickList)
if len(clickList)>=2:
print("we have path")
source = gridGraph.coordinateToNode(clickList[0])
target = gridGraph.coordinateToNode(clickList[1])
path = pathFinder.run(weights, source,target).path(pathType='coordinates')
visuimg = makeVisuImage(path,img)
implot.set_data(numpy.swapaxes(visuimg,0,1))
plt.draw()
bfreeze.on_clicked(freeze)
bunfreeze.on_clicked(unfreeze)
sgamma.on_changed(onslide)
cid = fig.canvas.mpl_connect('button_press_event', onclick)
plt.show()
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