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