+++ /dev/null
-from PIL import Image, ImageFilter, ImageChops
-from sorl.thumbnail import utils
-import re
-
-
-def dynamic_import(names):
- imported = []
- for name in names:
- # Use rfind rather than rsplit for Python 2.3 compatibility.
- lastdot = name.rfind('.')
- modname, attrname = name[:lastdot], name[lastdot + 1:]
- mod = __import__(modname, {}, {}, [''])
- imported.append(getattr(mod, attrname))
- return imported
-
-
-def get_valid_options(processors):
- """
- Returns a list containing unique valid options from a list of processors
- in correct order.
- """
- valid_options = []
- for processor in processors:
- if hasattr(processor, 'valid_options'):
- valid_options.extend([opt for opt in processor.valid_options
- if opt not in valid_options])
- return valid_options
-
-
-def colorspace(im, requested_size, opts):
- if 'bw' in opts and im.mode != "L":
- im = im.convert("L")
- elif im.mode not in ("L", "RGB", "RGBA"):
- im = im.convert("RGB")
- return im
-colorspace.valid_options = ('bw',)
-
-
-def autocrop(im, requested_size, opts):
- if 'autocrop' in opts:
- bw = im.convert("1")
- bw = bw.filter(ImageFilter.MedianFilter)
- # white bg
- bg = Image.new("1", im.size, 255)
- diff = ImageChops.difference(bw, bg)
- bbox = diff.getbbox()
- if bbox:
- im = im.crop(bbox)
- return im
-autocrop.valid_options = ('autocrop',)
-
-
-def scale_and_crop(im, requested_size, opts):
- x, y = [float(v) for v in im.size]
- xr, yr = [float(v) for v in requested_size]
-
- if 'crop' in opts or 'max' in opts:
- r = max(xr / x, yr / y)
- else:
- r = min(xr / x, yr / y)
-
- if r < 1.0 or (r > 1.0 and 'upscale' in opts):
- im = im.resize((int(x * r), int(y * r)), resample=Image.ANTIALIAS)
-
- crop = opts.get('crop') or 'crop' in opts
- if crop:
- # Difference (for x and y) between new image size and requested size.
- x, y = [float(v) for v in im.size]
- dx, dy = (x - min(x, xr)), (y - min(y, yr))
- if dx or dy:
- # Center cropping (default).
- ex, ey = dx / 2, dy / 2
- box = [ex, ey, x - ex, y - ey]
- # See if an edge cropping argument was provided.
- edge_crop = (isinstance(crop, basestring) and
- re.match(r'(?:(-?)(\d+))?,(?:(-?)(\d+))?$', crop))
- if edge_crop and filter(None, edge_crop.groups()):
- x_right, x_crop, y_bottom, y_crop = edge_crop.groups()
- if x_crop:
- offset = min(x * int(x_crop) / 100, dx)
- if x_right:
- box[0] = dx - offset
- box[2] = x - offset
- else:
- box[0] = offset
- box[2] = x - (dx - offset)
- if y_crop:
- offset = min(y * int(y_crop) / 100, dy)
- if y_bottom:
- box[1] = dy - offset
- box[3] = y - offset
- else:
- box[1] = offset
- box[3] = y - (dy - offset)
- # See if the image should be "smart cropped".
- elif crop == 'smart':
- left = top = 0
- right, bottom = x, y
- while dx:
- slice = min(dx, 10)
- l_sl = im.crop((0, 0, slice, y))
- r_sl = im.crop((x - slice, 0, x, y))
- if utils.image_entropy(l_sl) >= utils.image_entropy(r_sl):
- right -= slice
- else:
- left += slice
- dx -= slice
- while dy:
- slice = min(dy, 10)
- t_sl = im.crop((0, 0, x, slice))
- b_sl = im.crop((0, y - slice, x, y))
- if utils.image_entropy(t_sl) >= utils.image_entropy(b_sl):
- bottom -= slice
- else:
- top += slice
- dy -= slice
- box = (left, top, right, bottom)
- # Finally, crop the image!
- im = im.crop([int(v) for v in box])
- return im
-scale_and_crop.valid_options = ('crop', 'upscale', 'max')
-
-
-def filters(im, requested_size, opts):
- if 'detail' in opts:
- im = im.filter(ImageFilter.DETAIL)
- if 'sharpen' in opts:
- im = im.filter(ImageFilter.SHARPEN)
- return im
-filters.valid_options = ('detail', 'sharpen')
fnp / wolnelektury.git / blobdiff