def __init__(self, size, noComp):
self.noComp = noComp
self.default_width = 640
self.default_height = 480
self.rescale_ratio = 5
self.pca = eigenHands(size)
self.gabor = gaborFilters(False, size)
self.bgTotal = cv.CreateMat(70, 70, cv.CV_8UC3)
def __init__(self, size, noComp): self.noComp = noComp self.default_width = 640 self.default_height = 480 self.rescale_ratio = 5 self.pca = eigenHands(size) self.gabor = gaborFilters(False, size) self.bgTotal = cv.CreateMat(70, 70, cv.CV_8UC3)
def __init__(self, makeData, size):
self.pca = eigenHands(size)
#create the data matrix if they are not there
if(makeData == True):
self.pca.makeMatrix("garb")
self.pca.makeMatrix("hands")
self.pca.makeMatrix("rock")
self.pca.makeMatrix("paper")
self.pca.makeMatrix("scissors")
def __init__(self, size, makeData, noComp):
self.pca = eigenHands(size)
self.gabor = gaborFilters(False, size)
self.classify = classifyHands(False, size)
self.prep = preprocessing(size, noComp)
if (makeData == True):
self.pca.makeMatrix("garb")
self.pca.makeMatrix("hands")
self.pca.makeMatrix("rock")
self.pca.makeMatrix("paper")
self.pca.makeMatrix("scissors")
def __init__(self, size, makeData, noComp):
self.pca = eigenHands(size)
self.gabor = gaborFilters(False, size)
self.classify = classifyHands(False, size)
self.prep = preprocessing(size, noComp)
if(makeData == True):
self.pca.makeMatrix("garb")
self.pca.makeMatrix("hands")
self.pca.makeMatrix("rock")
self.pca.makeMatrix("paper")
self.pca.makeMatrix("scissors")
def __init__(self, makeData, size):
self.pca = eigenHands(size)
self.lambd = None
self.gamma = None
self.psi = None
self.theta = None
self.sigma = None
self.dim = None
if(makeData == True):
self.pca.makeMatrix("garb")
self.pca.makeMatrix("hands")
self.pca.makeMatrix("rock")
self.pca.makeMatrix("paper")
self.pca.makeMatrix("scissors")
def __init__(self, makeData, size):
self.pca = eigenHands(size)
self.lambd = None
self.gamma = None
self.psi = None
self.theta = None
self.sigma = None
self.dim = None
if (makeData == True):
self.pca.makeMatrix("garb")
self.pca.makeMatrix("hands")
self.pca.makeMatrix("rock")
self.pca.makeMatrix("paper")
self.pca.makeMatrix("scissors")
print "\t6 => do some classifications (SVN)"
print "\t7 => do some classifications (Knn)"
print "\t8 => create the FINAL models for classifiers"
print "\t9 => detect hands & predict\n"
choice = raw_input('your choice... ')
sizeImg = raw_input('the size of the training images ...')
build = raw_input('build the training matrixes (y/n) ...')
buildOpt = {'y':True, 'n':False}
print "\n"
#____________________________________________________________________________________________________
#____________________________________________________________________________________________________
#____________________________________________________________________________________________________
if(build == "y"):
datas = ['rock','paper','scissors','hands','garb']
for aset in datas:
hands = eigenHands(int(sizeImg))
hands.makeMatrix(aset)
#____________________________________________________________________________________________________
if(int(choice) == 1):
dataset = raw_input('choose the dataset c= > rock & paper & scissors; h => hands vs garbage ...')
noComp = raw_input('number of components for PCA ...')
datas = {'c':['rock','paper','scissors'], 'h':['hands','garb']}
hands = eigenHands(int(sizeImg))
_,X,_ = hands.justGetDataMat(datas[dataset][0],"",False)
hands.doPCA(X, int(noComp), "PCA/")
for i in range(0,len(datas[dataset])):
projData = hands.justGetDataMat(datas[dataset][i],"",True)
hands.projPCA(projData, False, "PCA/", datas[dataset][i])
#____________________________________________________________________________________________________
