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https://github.com/Hopiu/django-imagekit.git
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Crop doesn't necessarily imply the any scaling is taking place. Several ideas were discussed, from renaming Crop to combining both processors into a single Resize processor (as they were in the original IK), but those solutions were felt to either precluded future extension (alternative resize modes) or make the API too verbose.
124 lines
3.8 KiB
Python
124 lines
3.8 KiB
Python
from imagekit.lib import *
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class _Resize(object):
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width = None
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height = None
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def __init__(self, width=None, height=None):
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if width is not None:
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self.width = width
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if height is not None:
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self.height = height
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def process(self, img):
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raise NotImplementedError('process must be overridden by subclasses.')
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class Crop(_Resize):
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"""Resizes an image , cropping it to the specified width and height.
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"""
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TOP_LEFT = 'tl'
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TOP = 't'
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TOP_RIGHT = 'tr'
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BOTTOM_LEFT = 'bl'
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BOTTOM = 'b'
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BOTTOM_RIGHT = 'br'
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CENTER = 'c'
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LEFT = 'l'
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RIGHT = 'r'
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_ANCHOR_PTS = {
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TOP_LEFT: (0, 0),
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TOP: (0.5, 0),
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TOP_RIGHT: (1, 0),
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LEFT: (0, 0.5),
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CENTER: (0.5, 0.5),
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RIGHT: (1, 0.5),
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BOTTOM_LEFT: (0, 1),
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BOTTOM: (0.5, 1),
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BOTTOM_RIGHT: (1, 1),
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}
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def __init__(self, width=None, height=None, anchor=None):
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"""
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:param width: The target width, in pixels.
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:param height: The target height, in pixels.
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:param anchor: Specifies which part of the image should be retained when
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cropping. Valid values are:
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- Crop.TOP_LEFT
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- Crop.TOP
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- Crop.TOP_RIGHT
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- Crop.LEFT
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- Crop.CENTER
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- Crop.RIGHT
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- Crop.BOTTOM_LEFT
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- Crop.BOTTOM
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- Crop.BOTTOM_RIGHT
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"""
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super(Crop, self).__init__(width, height)
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self.anchor = anchor
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def process(self, img):
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cur_width, cur_height = img.size
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horizontal_anchor, vertical_anchor = Crop._ANCHOR_PTS[self.anchor or \
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Crop.CENTER]
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ratio = max(float(self.width)/cur_width, float(self.height)/cur_height)
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resize_x, resize_y = ((cur_width * ratio), (cur_height * ratio))
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crop_x, crop_y = (abs(self.width - resize_x), abs(self.height - resize_y))
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x_diff, y_diff = (int(crop_x / 2), int(crop_y / 2))
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box_left, box_right = {
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0: (0, self.width),
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0.5: (int(x_diff), int(x_diff + self.width)),
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1: (int(crop_x), int(resize_x)),
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}[horizontal_anchor]
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box_upper, box_lower = {
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0: (0, self.height),
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0.5: (int(y_diff), int(y_diff + self.height)),
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1: (int(crop_y), int(resize_y)),
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}[vertical_anchor]
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box = (box_left, box_upper, box_right, box_lower)
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img = img.resize((int(resize_x), int(resize_y)), Image.ANTIALIAS).crop(box)
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return img
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class Fit(_Resize):
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"""Resizes an image to fit within the specified dimensions.
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"""
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def __init__(self, width=None, height=None, upscale=None):
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"""
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:param width: The maximum width of the desired image.
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:param height: The maximum height of the desired image.
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:param upscale: A boolean value specifying whether the image should be
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enlarged if its dimensions are smaller than the target
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dimensions.
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"""
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super(Fit, self).__init__(width, height)
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self.upscale = upscale
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def process(self, img):
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cur_width, cur_height = img.size
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if not self.width is None and not self.height is None:
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ratio = min(float(self.width)/cur_width,
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float(self.height)/cur_height)
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else:
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if self.width is None:
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ratio = float(self.height)/cur_height
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else:
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ratio = float(self.width)/cur_width
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new_dimensions = (int(round(cur_width*ratio)),
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int(round(cur_height*ratio)))
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if new_dimensions[0] > cur_width or \
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new_dimensions[1] > cur_height:
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if not self.upscale:
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return img
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img = img.resize(new_dimensions, Image.ANTIALIAS)
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return img
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