# Source code for bob.ip.base.__functions__

```import math
import numpy

[docs]def angle_to_horizontal(right, left):
"""angle_to_horizontal(right, left) -> angle

Get the angle needed to level out (horizontally) two points.

**Parameters**

``right``, ``left`` : *(float, float)*
The two points to level out horizontically.

**Returns**

angle : *float*
The angle **in degrees** between the left and the right point
"""

return math.atan2(right[0] - left[0], right[1] - left[1]) * 180. / math.pi

[docs]def flip(src, dst = None):
"""flip(src, [dst]) -> dst

Flip a 2D or 3D array/image upside-down.
If given, the destination array ``dst`` should have the same size and type as the source array.

**Parameters**

``src`` : *array_like (2D or 3D)*
The source image to flip.

``dst`` : *array_like (2D or 3D)*
If given, the destination to flip ``src`` to.

**Returns**

``dst`` : *array_like (2D or 3D)*
The flipped image
"""
if dst is None:
dst = numpy.ndarray(src.shape, src.dtype)
dst[...,:,:] = src[...,::-1,:]
return dst

[docs]def flop(src, dst = None):
"""flop(src, [dst]) -> dst

Flip a 2D or 3D array/image left-right.
If given, the destination array ``dst`` should have the same size and type as the source array.

**Parameters**

``src`` : *array_like (2D or 3D)*
The source image to flip.

``dst`` : *array_like (2D or 3D)*
If given, the destination to flip ``src`` to.

**Returns**

``dst`` : *array_like (2D or 3D)*
The flipped image
"""
if dst is None:
dst = numpy.ndarray(src.shape, src.dtype)
dst[...,:] = src[...,::-1]
return dst

[docs]def crop(src, crop_offset, crop_size = None, dst = None, src_mask = None, dst_mask = None, fill_pattern = 0):

Crops the given image ``src`` image to the given offset (might be negative) and to the given size (might be greater than ``src`` image).

Either crop_size or dst need to be specified.
When masks are given, the need to be of the same size as the ``src`` and ``dst`` parameters.
When crop regions are outside the image, the cropped image will contain ``fill_pattern`` and the mask will be set to ``False``

**Parameters**

``src`` : *array_like (2D or 3D)*
The source image to flip.

``crop_offset`` : *(int, int)*
The position in ``src`` coordinates to start cropping; might be negative

``crop_size`` : *(int, int)*
The size of the cropped image; might be omitted when the ``dst`` is given

``dst`` : *array_like (2D or 3D)*
If given, the destination to crop ``src`` to.

Masks that define, where ``src`` and ``dst`` are valid

``fill_pattern``: *number*
[default: 0] The value to set outside the croppable area

**Returns**

``dst`` : *array_like (2D or 3D)*
The cropped image
"""
# check parameters
if dst is None:
dst = numpy.ndarray(src.shape[:-2] + crop_size, src.dtype)
elif crop_size is None:
crop_size = dst.shape[-2:]
else:
assert crop_size == dst.shape[-2:]

# get the real borders of both the source and the destination image
src_shape = src.shape[-2:]
src_offset = [max(crop_offset[i], 0) for i in range(2)]
src_size = [min(crop_size[i] + crop_offset[i], src_shape[i]) for i in range(2)]
dst_offset = [max(-crop_offset[i], 0) for i in range(2)]
dst_size = [min(dst_offset[i] + crop_size[i], src_size[i] + dst_offset[i] - src_offset[i]) for i in range(2)]

# copy data
dst.fill(fill_pattern)
dst[...,dst_offset[0]:dst_size[0], dst_offset[1]:dst_size[1]] = src[...,src_offset[0]:src_size[0], src_offset[1]:src_size[1]]

return dst

[docs]def shift(src, offset, dst = None, src_mask = None, dst_mask = None, fill_pattern = 0):

Shifts the given image ``src`` image with the given offset (might be negative).

If ``dst`` is specified, the image is shifted into the ``dst`` image.
Ideally, ``dst`` should have the same size as ``src``, but other sizes work as well.
When ``dst`` is ``None`` (the default), it is created in the same size as ``src``.
When masks are given, the need to be of the same size as the ``src`` and ``dst`` parameters.
When shift to regions are outside the image, the shifted image will contain ``fill_pattern`` and the mask will be set to ``False``

**Parameters**

``src`` : *array_like (2D or 3D)*
The source image to flip.

``crop_offset`` : *(int, int)*
The position in ``src`` coordinates to start cropping; might be negative

``crop_size`` : *(int, int)*
The size of the cropped image; might be omitted when the ``dst`` is given

``dst`` : *array_like (2D or 3D)*
If given, the destination to crop ``src`` to.

Masks that define, where ``src`` and ``dst`` are valid

``fill_pattern``: *number*
[default: 0] The value to set outside the croppable area

**Returns**

``dst`` : *array_like (2D or 3D)*
The cropped image
"""
# check parameters
if dst is None:
dst = numpy.ndarray(src.shape, src.dtype)

# shift image by cropping