예제 #1
0
print folder
trainDirect     = folder+"tempTrain/"
trainNP         = folder+"tempTrainNP/"
testDirect      = folder+"tempTest/"
testNP          = folder+"tempTestNP/"

"""Load the train/test split information"""
trainFs, testFs     = helperFuncs.getTrainTestSplit(True,folder)

trainL  = len(trainFs)
testL   = len(testFs)


features,labels     = helperFuncs.getTargets(outType) #get the OCR vector for each CID
outsize             = len(features[features.keys()[0]]) #this it the size of the target (# of OCRfeatures)
means,stds          = helperFuncs.getMeansStds(features)


"""load model"""
model   = helperFuncs.loadModel(folder+"wholeModel")


while not isfile(testNP+"Xtest.h5"):
    print "sleeping because Test folder empty             \r",
    time.sleep(1.)
print ""

print "Loading np test arrays" 

loadedUp    = False
while not loadedUp:       
예제 #2
0
def getSize(folder):
    fold 	= folder[folder[-1].rfind("/")+1:]
    fold 	= fold[:fold.find("_")]
    print fold
    fold 	= fold[fold.rfind("/")+1:]
    print fold
    return fold

with open(sys.argv[1]+"wholeModel.pickle",'rb') as f:
    model   = cPickle.load(f)
    
size 	= int(getSize(sys.argv[1]))
imdim   = size
#OCRfeatures, labels     = getOCRScaledTargets()
OCRTargets, labels  = getOCRTargets()
means,stds  = getMeansStds()
    
    
if True:
    ld  = listdir("/home/test/usan/")
    images  = np.zeros((1,1,imdim,imdim),dtype=np.float)
    for x in ld:
        print x
        try:
            CID     = x
            print "reading in"
            image   = io.imread("/home/test/usan/"+x,as_grey=True)
            image   = minusOnes(image)
            print "numpying"
            image   = np.array(image)
            #image   = convertIt(image)
예제 #3
0
    fold = folder[folder[-1].rfind("/") + 1:]
    fold = fold[:fold.find("_")]
    print fold
    fold = fold[fold.rfind("/") + 1:]
    print fold
    return fold


with open(sys.argv[1] + "wholeModel.pickle", 'rb') as f:
    model = cPickle.load(f)

size = int(getSize(sys.argv[1]))
imdim = size
#OCRfeatures, labels     = getOCRScaledTargets()
OCRTargets, labels = getOCRTargets()
means, stds = getMeansStds()

if True:
    ld = listdir("/home/test/usan/")
    images = np.zeros((1, 1, imdim, imdim), dtype=np.float)
    for x in ld:
        print x
        try:
            CID = x
            print "reading in"
            image = io.imread("/home/test/usan/" + x, as_grey=True)
            image = minusOnes(image)
            print "numpying"
            image = np.array(image)
            #image   = convertIt(image)
            print "resizing"
예제 #4
0
print folder
trainDirect     = folder+"tempTrain/"
trainNP         = folder+"tempTrainNP/"
testDirect      = folder+"tempTest/"
testNP          = folder+"tempTestNP/"

"""Load the train/test split information"""
trainFs, testFs     = helperFuncs.getTrainTestSplit(True,folder)

trainL  = len(trainFs)
testL   = len(testFs)


features,labels     = helperFuncs.getTargets(outType) #get the OCR vector for each CID
outsize             = len(features[features.keys()[0]]) #this it the size of the target (# of OCRfeatures)
means,stds          = helperFuncs.getMeansStds()


"""load model"""
#with open(folder+"bestModel.pickle",'rb') as f:
#    model     = cPickle.load(f)

model   = helperFuncs.loadModel(folder+"wholeModel")


while not isfile(testNP+"Xtest.h5"):
    print "sleeping because Test folder empty             \r",
    time.sleep(1.)
print ""

print "Loading np test arrays"