X-Git-Url: https://git.mdrn.pl/redakcja.git/blobdiff_plain/42faac096df5479bd7747d9068eb88d1410d6d34..aa021ad04c81969c58558343fb1ff2409c82563e:/apps/sorl/thumbnail/processors.py

diff --git a/apps/sorl/thumbnail/processors.py b/apps/sorl/thumbnail/processors.py
deleted file mode 100644
index a6c17416..00000000
--- a/apps/sorl/thumbnail/processors.py
+++ /dev/null
@@ -1,130 +0,0 @@
-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')