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createBrodatz32Dataset.py
31 lines (24 loc) · 1.39 KB
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createBrodatz32Dataset.py
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from ConvnetDataset import *
def getBrodatzClasses():
return ['bark', 'beachsand', 'beans', 'burlap', 'd10', 'd11', 'd4', 'd5', 'd51',
'd52', 'd6', 'd95', 'fieldstone', 'grass', 'ice', 'image09', 'image15', 'image17',
'image19', 'paper', 'peb54', 'pigskin', 'pressedcl', 'raffia', 'raffia2',
'reptile', 'ricepaper', 'seafan', 'straw2', 'tree', 'water', 'woodgrain']
def createDatasetBrodatz(fold):
sourceFolder = '/home/especial/vri/databases/brodatz/as_png'
saveFolder = '/home/ppginf/lghafemann/nobackup/data/brodatz_1batch_%d' % fold
expectedDistribution = [0.3, 0.2, 0.5]
classNames = getBrodatzClasses()
classNumbers = range(len(classNames))
ConvnetDataset.CreateConvNetDataset(SourceFolder = sourceFolder,
TargetFolder = saveFolder,
ExpectedDistribution = expectedDistribution,
GetLabelsFrom = LabelFromList(classNames),
Classes = classNumbers,
ClassNames = classNames,
SplitFunction = GroupingSplit(),
Grayscale = True,
NumTrainBatches = 1)
if __name__ == '__main__':
createDatasetBrodatz(2)
createDatasetBrodatz(3)