# generate features
imagePixelFeatures = FeatureGenerator.generatePixelFeaturesForImage(ex.m_img)
# For each feature, how many distinct values?
for i in range(imagePixelFeatures.shape[1]):
print "Feature %d has %d distinct values" \
% (i, len(np.unique( imagePixelFeatures[:,i])) )
# Plot a selection of features
sel = np.arange(26,30)
# sel = range(80,86)
# colours have to be on range 0-1
plt.figure()
# just plot some of the data for clarity
nbpts = 2000
ptsz = 5
whichPts = np.random.choice( imagePixelFeatures.shape[0], nbpts, replace=False)
# python weirdness, can't index from 2 lists at once...
subset = imagePixelFeatures[whichPts,:]
subset = subset[:,sel]
labelSubset = np.reshape(ex.m_gt, (imagePixelFeatures.shape[0],1))[whichPts].squeeze()
print labelSubset.shape
# todo: fix bug, displayed labels not right, car cluster should be lower right
amntools.gplotmatrix( subset,\
labelSubset, \
#ex.m_gt.flatten(1)[whichPts], \
msize=ptsz, classColours=clrs)
plt.show()
if args.labs.endswith('.pkl'):
labs = pomio.unpickleObject( args.labs )
else:
labs = pomio.readMatFromCSV( args.labs ).astype(np.int32)
# show labels
if labs != None:
plt.figure()
plt.hist( labs, pomio.getNumClasses() )
plt.title('Class counts')
plt.xticks( range(pomio.getNumClasses()),
pomio.getClasses()[:pomio.getNumClasses()],
size='small' )
# show at most 9 features at once
fstarts = range( args.nstart, D, args.nshow )
plt.figure()
for fs in fstarts:
fend = min(D-1,fs+args.nshow-1)
print ' Displaying features %d-%d:' % (fs, fend)
rng = range( fs, fend+1 )
fnames = [ 'F%d' % x for x in rng ]
amntools.gplotmatrix( ftrs[:,rng], labs, featureNames=fnames )
plt.waitforbuttonpress()
plt.interactive(0)
plt.show()
imagePixelFeatures = FeatureGenerator.generatePixelFeaturesForImage(ex.m_img)
# For each feature, how many distinct values?
for i in range(imagePixelFeatures.shape[1]):
print "Feature %d has %d distinct values" \
% (i, len(np.unique( imagePixelFeatures[:,i])) )
# Plot a selection of features
sel = np.arange(12, 29, 2)
# sel = range(80,86)
# colours have to be on range 0-1
plt.figure()
# just plot some of the data for clarity
nbpts = 2000
ptsz = 5
whichPts = np.random.choice(imagePixelFeatures.shape[0], nbpts, replace=False)
# python weirdness, can't index from 2 lists at once...
subset = imagePixelFeatures[whichPts, :]
subset = subset[:, sel]
labelSubset = np.reshape(ex.m_gt,
(imagePixelFeatures.shape[0], 1))[whichPts].squeeze()
print labelSubset.shape
# todo: fix bug, displayed labels not right, car cluster should be lower right
amntools.gplotmatrix( subset,\
labelSubset, \
#ex.m_gt.flatten(1)[whichPts], \
msize=ptsz, classColours=clrs)
plt.show()
labs = None
else:
if args.labs.endswith('.pkl'):
labs = pomio.unpickleObject(args.labs)
else:
labs = pomio.readMatFromCSV(args.labs).astype(np.int32)
# show labels
if labs != None:
plt.figure()
plt.hist(labs, pomio.getNumClasses())
plt.title('Class counts')
plt.xticks(range(pomio.getNumClasses()),
pomio.getClasses()[:pomio.getNumClasses()],
size='small')
# show at most 9 features at once
fstarts = range(args.nstart, D, args.nshow)
plt.figure()
for fs in fstarts:
fend = min(D - 1, fs + args.nshow - 1)
print ' Displaying features %d-%d:' % (fs, fend)
rng = range(fs, fend + 1)
fnames = ['F%d' % x for x in rng]
amntools.gplotmatrix(ftrs[:, rng], labs, featureNames=fnames)
plt.waitforbuttonpress()
plt.interactive(0)
plt.show()
