Esempi in Python per loadAllTrainingData

Esempio n. 1

File: ann_Nlayers_Real_Data.py Progetto: MauriceGit/Artificial_Neural_Network_Character_Classification

                                #################
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                                        #
                     
                     
########################################################################
# Trainings- und Testdaten einlesen!
########################################################################

basePath	  = "../"
trainingFiles = ["Trainingsdaten.pat"]
testFiles     = ["Handschriften-Sommersemester-2015.pat"] 
#testFiles     = ["TestWindowsSchrift.pat"] 
testDataCount = 260

images_and_labels = loadAllTrainingData(trainingFiles, basePath)
images  = parseImagesFromData(images_and_labels)
targets = parseTargetsFromData(images_and_labels)

test_images_and_labels = loadAllTrainingData(testFiles, basePath)
test_images  = parseImagesFromData(test_images_and_labels)
test_targets = parseTargetsFromData(test_images_and_labels)

X = np.array(reduceDimensionByOne(images[:testDataCount]))
y = np.array(targets[:testDataCount])

testData = []
for i in range(len(test_images)):
    testData.append(flattenFieldToArray(test_images[i]))

########################################################################

Esempio n. 2

File: ann_Nlayers_Real_Data_automated_learning.py Progetto: MauriceGit/Artificial_Neural_Network_Character_Classification

                            #########################
                                #################
                                    #########
                                        #
                     
                     
########################################################################
# Trainings- und Testdaten einlesen!
########################################################################

#trainingFiles = ["Trainingsdaten.pat"]
trainingFiles = ["Trainingsdaten.pat", "Handschriften-Sommersemester-2015_01.pat", "Handschriften-Sommersemester-2015_02.pat", "TestHandschriften.pat"]
#testFiles     = ["Handschriften-Sommersemester-2015_02.pat"] 
testFiles     = ["TestWindowsSchrift.pat"] 

images_and_labels = loadAllTrainingData(trainingFiles, "/home/maurice/Uni/Master/Learning_Softcomputing/src/")
images  = parseImagesFromData(images_and_labels)
targets = parseTargetsFromData(images_and_labels)

test_images_and_labels = loadAllTrainingData(testFiles, "/home/maurice/Uni/Master/Learning_Softcomputing/src/")
test_images  = parseImagesFromData(test_images_and_labels)
test_targets = parseTargetsFromData(test_images_and_labels)

X = np.array(reduceDimensionByOne(images[:260]))
y = np.array(targets[:260])

testData = []
for i in range(len(test_images)):
    testData.append(flattenFieldToArray(test_images[i]))
    
########################################################################