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Update __init__.py #26

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94 changes: 46 additions & 48 deletions patchify/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,11 +3,9 @@
"""

from typing import Tuple, Union, cast

import numpy as np
from .view_as_windows import view_as_windows


Imsize = Union[Tuple[int, int], Tuple[int, int, int]]


Expand All @@ -17,14 +15,16 @@ def patchify(image: np.ndarray, patch_size: Imsize, step: int = 1) -> np.ndarray

Parameters
----------
image: the image to be split. It can be 2d (m, n) or 3d (k, m, n)
image: the image to be split. It can be 2D (m, n) or 3D (k, m, n)
patch_size: the size of a single patch
step: the step size between patches

Examples
--------
>>> image = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
>>> patches = patchify(image, (2, 2), step=1) # split image into 2*3 small 2*2 patches.
>>> image = np.array([[1, 2, 3, 4],
... [5, 6, 7, 8],
... [9, 10, 11, 12]])
>>> patches = patchify(image, (2, 2), step=1) # split into 2×3 small 2×2 patches
>>> assert patches.shape == (2, 3, 2, 2)
>>> reconstructed_image = unpatchify(patches, image.shape)
>>> assert (reconstructed_image == image).all()
Expand All @@ -34,42 +34,43 @@ def patchify(image: np.ndarray, patch_size: Imsize, step: int = 1) -> np.ndarray

def unpatchify(patches: np.ndarray, imsize: Imsize) -> np.ndarray:
"""
Merge patches into the orignal image
Merge patches into the original image.

Parameters
----------
patches: the patches to merge. It can be patches for a 2d image (k, l, m, n)
or 3d volume (i, j, k, l, m, n)
patches: patches to merge. Can be patches for a 2D image (k, l, m, n)
or 3D volume (i, j, k, l, m, n)
imsize: the size of the original image or volume

Examples
--------
>>> image = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
>>> patches = patchify(image, (2, 2), step=1) # split image into 2*3 small 2*2 patches.
>>> image = np.array([[1, 2, 3, 4],
... [5, 6, 7, 8],
... [9, 10, 11, 12]])
>>> patches = patchify(image, (2, 2), step=1) # split into 2×3 small 2×2 patches
>>> assert patches.shape == (2, 3, 2, 2)
>>> reconstructed_image = unpatchify(patches, image.shape)
>>> assert (reconstructed_image == image).all()
"""

assert len(patches.shape) / 2 == len(
assert len(patches.shape) // 2 == len(
imsize
), "The patches dimension is not equal to the original image size"
), "The patches dimension does not match the original image size"

if len(patches.shape) == 4:
return _unpatchify2d(patches, cast(Tuple[int, int], imsize))
elif len(patches.shape) == 6:
return _unpatchify3d(patches, cast(Tuple[int, int, int], imsize))
else:
raise NotImplementedError(
"Unpatchify only supports a matrix of 2D patches (k, l, m, n)"
"Unpatchify only supports matrices of 2D patches (k, l, m, n) "
f"or 3D volumes (i, j, k, l, m, n), but got: {patches.shape}"
)


def _unpatchify2d( # pylint: disable=too-many-locals
patches: np.ndarray, imsize: Tuple[int, int]
) -> np.ndarray:

def _unpatchify2d(patches: np.ndarray, imsize: Tuple[int, int]) -> np.ndarray:
"""
Reconstruct a 2D image from its patches.
"""
assert len(patches.shape) == 4

i_h, i_w = imsize
Expand All @@ -80,8 +81,8 @@ def _unpatchify2d( # pylint: disable=too-many-locals
s_w = 0 if n_w <= 1 else (i_w - p_w) / (n_w - 1)
s_h = 0 if n_h <= 1 else (i_h - p_h) / (n_h - 1)

# The step size should be same for all patches, otherwise the patches are unable
# to reconstruct into a image
# The step size should be the same for all patches; otherwise,
# the patches cannot reconstruct into a valid image
if int(s_w) != s_w:
raise NonUniformStepSizeError(i_w, n_w, p_w, s_w)
if int(s_h) != s_h:
Expand All @@ -90,31 +91,27 @@ def _unpatchify2d( # pylint: disable=too-many-locals
s_h = int(s_h)

i, j = 0, 0

while True:
i_o, j_o = i * s_h, j * s_w

image[i_o : i_o + p_h, j_o : j_o + p_w] = patches[i, j]
i_o, j_o = int(i * s_h), int(j * s_w)
image[int(i_o): int(i_o + p_h), int(j_o): int(j_o + p_w)] = patches[i, j]

if j < n_w - 1:
j = min((j_o + p_w) // s_w, n_w - 1)
j = min(int((j_o + p_w) // s_w), n_w - 1)
elif i < n_h - 1 and j >= n_w - 1:
# Go to next row
i = min((i_o + p_h) // s_h, n_h - 1)
i = min(int((i_o + p_h) // s_h), n_h - 1)
j = 0
elif i >= n_h - 1 and j >= n_w - 1:
# Finished
break
else:
raise RuntimeError("Unreachable")

return image


def _unpatchify3d( # pylint: disable=too-many-locals
patches: np.ndarray, imsize: Tuple[int, int, int]
) -> np.ndarray:

def _unpatchify3d(patches: np.ndarray, imsize: Tuple[int, int, int]) -> np.ndarray:
"""
Reconstruct a 3D volume from its patches.
"""
assert len(patches.shape) == 6

i_h, i_w, i_c = imsize
Expand All @@ -126,8 +123,8 @@ def _unpatchify3d( # pylint: disable=too-many-locals
s_h = 0 if n_h <= 1 else (i_h - p_h) / (n_h - 1)
s_c = 0 if n_c <= 1 else (i_c - p_c) / (n_c - 1)

# The step size should be same for all patches, otherwise the patches are unable
# to reconstruct into a image
# The step size should be the same for all patches; otherwise,
# the patches cannot reconstruct into a valid volume
if int(s_w) != s_w:
raise NonUniformStepSizeError(i_w, n_w, p_w, s_w)
if int(s_h) != s_h:
Expand All @@ -140,24 +137,20 @@ def _unpatchify3d( # pylint: disable=too-many-locals
s_c = int(s_c)

i, j, k = 0, 0, 0

while True:

i_o, j_o, k_o = i * s_h, j * s_w, k * s_c

image[i_o : i_o + p_h, j_o : j_o + p_w, k_o : k_o + p_c] = patches[i, j, k]
i_o, j_o, k_o = int(i * s_h), int(j * s_w), int(k * s_c)
image[int(i_o): int(i_o + p_h), int(j_o): int(j_o + p_w), int(k_o): int(k_o + p_c)] = patches[i, j, k]

if k < n_c - 1:
k = min((k_o + p_c) // s_c, n_c - 1)
k = min(int((k_o + p_c) // s_c), n_c - 1)
elif j < n_w - 1 and k >= n_c - 1:
j = min((j_o + p_w) // s_w, n_w - 1)
j = min(int((j_o + p_w) // s_w), n_w - 1)
k = 0
elif i < n_h - 1 and j >= n_w - 1 and k >= n_c - 1:
i = min((i_o + p_h) // s_h, n_h - 1)
i = min(int((i_o + p_h) // s_h), n_h - 1)
j = 0
k = 0
elif i >= n_h - 1 and j >= n_w - 1 and k >= n_c - 1:
# Finished
break
else:
raise RuntimeError("Unreachable")
Expand All @@ -166,18 +159,23 @@ def _unpatchify3d( # pylint: disable=too-many-locals


class NonUniformStepSizeError(RuntimeError):
def __init__(
self, imsize: int, n_patches: int, patch_size: int, step_size: float
) -> None:
"""
Raised when patch reconstruction requires a non-integer step size.
"""
def __init__(self, imsize: int, n_patches: int, patch_size: int, step_size: float) -> None:
super().__init__(imsize, n_patches, patch_size, step_size)
self.n_patches = n_patches
self.patch_size = patch_size
self.imsize = imsize
self.step_size = step_size

def __repr__(self) -> str:
return f"Unpatchify only supports reconstructing image with a uniform step size for all patches. \
However, reconstructing {self.n_patches} x {self.patch_size}px patches to an {self.imsize} image requires {self.step_size} as step size, which is not an integer."
return (
f"Unpatchify only supports reconstructing with a uniform step size for all patches. "
f"However, reconstructing {self.n_patches} × {self.patch_size} patches "
f"to an image/volume of size {self.imsize} requires a step size of {self.step_size}, "
"which is not an integer."
)

def __str__(self) -> str:
return self.__repr__()