Image Data Generator Zoom Range. Then calling image dataset from directory main directory labels inferred will return a tf data dataset that yields batches of images from the subdirectories class a and class b together with labels 0 and 1 0 corresponding to class a and 1 corresponding to class b. If scalar z zoom will be randomly picked in the range 1 z 1 z.
A sequence of two can be passed instead to select this range. To x and y zoom range. Image data generator featurewise center false samplewise center false featurewise std normalization false.
Image data generator featurewise center false samplewise center false featurewise std normalization false.
X label self. Only to x. For example zoom range is equal to 0 5 means that the zooming factor will be chosen from the range 0 5 1 5. Convert the data into a numpy array then preprocess it by scaling all pixel intensities to the range 0 1 data np array data dtype float 255 0 encode the labels which are currently strings as integers and then one hot encode them le labelencoder labels le fit transform labels labels to categorical labels 2 partition the data into training and testing splits.