def shear_y(image, level, fill_value):
"""Equivalent of PIL Shearing in Y dimension."""
# Shear parallel to y axis is a projective transform
# with a matrix form of:
# [1 0
# level 1].
image = tfi.transform(wrap(image), [1., 0., 0., level, 1., 0., 0., 0.])
return unwrap(image, fill_value)
def shear_y(image: TensorLike, level: float, replace: int) -> TensorLike:
"""Perform shear operation on an image (y-axis)
Args:
image: A 3D image Tensor.
level: A float denoting shear element along x-axis
replace: A one or three value 1D tensor to fill empty pixels.
Returns:
Transformed image along X or Y axis, with space outside image
filled with replace.
"""
# Shear parallel to y axis is a projective transform
# with a matrix form of:
# [1 0
# level 1].
image = transform(wrap(image), [1.0, 0.0, 0.0, level, 1.0, 0.0, 0.0, 0.0])
return unwrap(image, replace)
def translate_xy(image: TensorLike, translate_to: TensorLike,
replace: int) -> TensorLike:
"""Translates image in X or Y dimension.
Args:
image: A 3D image Tensor.
translate_to: A 1D tensor to translate [x, y]
replace: A one or three value 1D tensor to fill empty pixels.
Returns:
Translated image along X or Y axis, with space outside image
filled with replace.
Raises:
ValueError: if axis is neither 0 nor 1."""
image = wrap(image)
trans = tf.convert_to_tensor(translate_to)
image = translate(image, [trans.numpy()[0], 0])
image = translate(image, [0, trans.numpy()[1]])
return unwrap(image, replace)
def rotate(image, degrees, fill_value, interpolation='BILINEAR'):
"""Rotates the image by degrees either clockwise or counterclockwise.
Args:
image: An image Tensor of type uint8.
degrees: Float, a scalar angle in degrees to rotate all images by. If degrees is positive the image
will be rotated clockwise otherwise it will be rotated counterclockwise.
fill_value: A one or three value 1D tensor to fill empty pixels caused by the rotate operation.
interpolation: Interpolation method
Returns:
The rotated version of image.
"""
# Convert from degrees to radians.
degrees_to_radians = math.pi / 180.0
radians = degrees * degrees_to_radians
# In practice, we should randomize the rotation degrees by flipping
# it negatively half the time, but that's done on 'degrees' outside
# of the function.
image = tfi.rotate(wrap(image), radians, interpolation=interpolation)
return unwrap(image, fill_value)
def translate_y(image, pixels, fill_value):
"""Equivalent of PIL Translate in Y dimension."""
image = tfi.translate(wrap(image), [0, -pixels])
return unwrap(image, fill_value)
