def classifyImageSuperPixels( rgbImage, classifier, superPixelObj, ftype, aggtype, makeProbabilities ):
outProbs = None
# Get superpixels
imgSuperPixelsMask = superPixelObj.m_labels
imgSuperPixels = superPixelObj.m_nodes
numberImgSuperPixels = len(imgSuperPixels)
print "**Image contains", numberImgSuperPixels, "superpixels"
# Get superpixel features
# todo: replace with features.computeSuperPixelFeatures JRS
spFtrs = features.computeSuperPixelFeatures( rgbImage, superPixelObj, ftype, aggtype )
spLabels = classLabelsOfFeatures( spFtrs, classifier )
if makeProbabilities:
outProbs = classProbsOfFeatures( spFtrs, classifier )
return (spLabels, outProbs)
superPixelCompactness = args.superPixelCompactness
imgRGB = amntools.readImage(args.infile)
# Turn image into superpixels.
spix = superPixels.computeSuperPixelGraph(
imgRGB, 'slic', [numberSuperPixels, superPixelCompactness])
print 'Loading classifier...'
assert args.clfrFn != None, 'No classifier filename specified!'
clfr = pomio.unpickleObject(args.clfrFn)
print 'Computing superpixel features...'
ftrs = features.computeSuperPixelFeatures(imgRGB,
spix,
ftype='classic',
aggtype='classic')
print 'Computing class probabilities...'
classProbs = classification.classProbsOfFeatures(ftrs,clfr,\
requireAllClasses=False)
if args.verbose:
plt.interactive(1)
if adjProbs != None:
plt.figure()
plt.imshow(np.log(1 + adjProbs),
cmap=cm.get_cmap('gray'),
interpolation='none')
plt.title('Adjacency probabilities')
numberSuperPixels = args.nbSuperPixels
superPixelCompactness = args.superPixelCompactness
imgRGB = amntools.readImage( args.infile )
# Turn image into superpixels.
spix = superPixels.computeSuperPixelGraph( imgRGB, 'slic', [numberSuperPixels,superPixelCompactness] )
print 'Loading classifier...'
assert args.clfrFn != None, 'No classifier filename specified!'
clfr = pomio.unpickleObject(args.clfrFn)
print 'Computing superpixel features...'
ftrs = features.computeSuperPixelFeatures( imgRGB, spix, ftype='classic', aggtype='classic' )
print 'Computing class probabilities...'
classProbs = classification.classProbsOfFeatures(ftrs,clfr,\
requireAllClasses=False)
if args.verbose:
plt.interactive(1)
if adjProbs != None:
plt.figure()
plt.imshow(np.log(1+adjProbs), cmap=cm.get_cmap('gray'), interpolation='none')
plt.title('Adjacency probabilities')
plt.waitforbuttonpress()