def ReadImage( fname ):
mg = Image.open( fname )
r,g,b = mg.split()
h,v = r.size
data = zeros( (v,h,3), float )
data[:,:,0] = akando.i2a( r )/255.
data[:,:,1] = akando.i2a( g )/255.
data[:,:,2] = akando.i2a( b )/255.
return data
def ReadImage(fname):
mg = Image.open(fname)
r, g, b = mg.split()
h, v = r.size
data = zeros((v, h, 3), float)
data[:, :, 0] = akando.i2a(r) / 255.
data[:, :, 1] = akando.i2a(g) / 255.
data[:, :, 2] = akando.i2a(b) / 255.
return data
def SortRun( mglist, K ):
N = len( mglist )
D = 128**2 # word length of 7
data = zeros( (N,D), float )
for i in range( N ):
mg = Image.open( mglist[i] )
d = akando.i2a( mg )/255.
data[i] = ravel( d + 0 )
# perform k-means
clusts1 = kmeans.Init2( K, data )
ok = 1
while ok:
mmb = kmeans.AssignMembership( clusts1, data )
clusts2 = kmeans.ClusterAverage( mmb, data )
diff = ( abs( ravel(clusts1)-ravel(clusts2))).sum()
if diff==0:
ok = 0
clusts1 = clusts2 + 0
print diff
return clusts1, data
def SortRun(mglist, K):
N = len(mglist)
D = 128**2 # word length of 7
data = zeros((N, D), float)
for i in range(N):
mg = Image.open(mglist[i])
d = akando.i2a(mg) / 255.
data[i] = ravel(d + 0)
# perform k-means
clusts1 = kmeans.Init2(K, data)
ok = 1
while ok:
mmb = kmeans.AssignMembership(clusts1, data)
clusts2 = kmeans.ClusterAverage(mmb, data)
diff = (abs(ravel(clusts1) - ravel(clusts2))).sum()
if diff == 0:
ok = 0
clusts1 = clusts2 + 0
print diff
return clusts1, data
def LoadImages(dr, mglist):
pics = []
for i in mglist:
mg = Image.open(dr + '/' + i)
pics.append(akando.i2a(mg) / 256.)
return pics
def LoadImages( dr, mglist ):
pics = []
for i in mglist:
mg = Image.open( dr +'/' + i )
pics.append( akando.i2a( mg )/256. )
return pics
