TensorFlow 2 version
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Applies an affine transformation specified by the parameters given.
tf.keras.preprocessing.image.apply_affine_transform(
x, theta=0, tx=0, ty=0, shear=0, zx=1, zy=1, row_axis=0, col_axis=1,
channel_axis=2, fill_mode='nearest', cval=0.0, order=1
)
Arguments
x: 2D numpy array, single image.
theta: Rotation angle in degrees.
tx: Width shift.
ty: Heigh shift.
shear: Shear angle in degrees.
zx: Zoom in x direction.
zy: Zoom in y direction
row_axis: Index of axis for rows in the input image.
col_axis: Index of axis for columns in the input image.
channel_axis: Index of axis for channels in the input image.
fill_mode: Points outside the boundaries of the input
are filled according to the given mode
(one of `{'constant', 'nearest', 'reflect', 'wrap'}`).
cval: Value used for points outside the boundaries
of the input if `mode='constant'`.
order: int, order of interpolation
Returns
The transformed version of the input.