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Use box for reduce

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This commit is contained in:
Alexander 2019-12-20 14:54:06 +03:00
parent fa9e85cd1f
commit b85c610a03
1 changed files with 30 additions and 9 deletions
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39
src/PIL/Image.py
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@ -144,6 +144,9 @@ HAMMING = 5
BICUBIC = CUBIC = 3
LANCZOS = ANTIALIAS = 1
_filters_support = {BOX: 0.5, BILINEAR: 1.0, HAMMING: 1.0, BICUBIC: 2.0, LANCZOS: 3.0}
# dithers
NEAREST = NONE = 0
ORDERED = 1 # Not yet implemented
@ -1764,6 +1767,23 @@ class Image:
return m_im
def _get_safe_box(self, size, resample, box):
"""Expands the box so it includes neighboring pixels
that could be used by resampling with the given resampling filter.
"""
filter_support = _filters_support[resample] - 0.5
scale_x = (box[2] - box[0]) / size[0]
scale_y = (box[3] - box[1]) / size[1]
support_x = filter_support * scale_x
support_y = filter_support * scale_y
return (
max(0, int(box[0] - support_x)),
max(0, int(box[1] - support_y)),
min(self.size[0], math.ceil(box[2] + support_x)),
min(self.size[1], math.ceil(box[3] + support_y)),
)
def resize(self, size, resample=NEAREST, box=None, max_reduce=None):
"""
Returns a resized copy of this image.
@ -1815,7 +1835,7 @@ class Image:
)
if max_reduce is not None and max_reduce < 1.0:
raise ValueError('max_reduce could not be less than 1.0')
raise ValueError("max_reduce could not be less than 1.0")
size = tuple(size)
@ -1838,15 +1858,16 @@ class Image:
self.load()
if max_reduce is not None and resample != NEAREST:
x_factor = int((box[2] - box[0]) / size[0] / max_reduce) or 1
y_factor = int((box[3] - box[1]) / size[1] / max_reduce) or 1
if x_factor > 1 or y_factor > 1:
self = self.reduce((x_factor, y_factor))
factor_x = int((box[2] - box[0]) / size[0] / max_reduce) or 1
factor_y = int((box[3] - box[1]) / size[1] / max_reduce) or 1
if factor_x > 1 or factor_y > 1:
reduce_box = self._get_safe_box(size, resample, box)
self = self.reduce((factor_x, factor_y), box=reduce_box)
box = (
box[0] / x_factor,
box[1] / y_factor,
box[2] / x_factor,
box[3] / y_factor,
(box[0] - reduce_box[0]) / factor_x,
(box[1] - reduce_box[1]) / factor_y,
(box[2] - reduce_box[0]) / factor_x,
(box[3] - reduce_box[1]) / factor_y,
)
return self._new(self.im.resize(size, resample, box))