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):
"""crop(src, crop_offset, crop_size, [dst], [src_mask], [dst_mask], [fill_pattern]) -> dst
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.
``src_mask``, ``dst_mask``: *array_like(bool, 2D or 3D)*
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]]
# set mask data
if src_mask is not None and dst_mask is not None:
assert src_mask.shape == src.shape
assert dst_mask.shape == dst.shape
dst_mask.fill(False)
dst_mask[...,dst_offset[0]:dst_size[0], dst_offset[1]:dst_size[1]] = src_mask[...,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):
"""shift(src, offset, [dst], [src_mask], [dst_mask], [fill_pattern]) -> dst
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.
``src_mask``, ``dst_mask``: *array_like(bool, 2D or 3D)*
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
return crop(src, offset, dst=dst, src_mask=src_mask, dst_mask=dst_mask, fill_pattern=fill_pattern)