images-demo/image_transformer.py

   1 #!/usr/bin/python2.5
   2 #
   3 # Copyright 2008 Google Inc.
   4 #
   5 # Licensed under the Apache License, Version 2.0 (the "License");
   6 # you may not use this file except in compliance with the License.
   7 # You may obtain a copy of the License at
   8 #
   9 #      http://www.apache.org/licenses/LICENSE-2.0
  10 #
  11 # Unless required by applicable law or agreed to in writing, software
  12 # distributed under the License is distributed on an "AS IS" BASIS,
  13 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  14 # See the License for the specific language governing permissions and
  15 # limitations under the License.
  16
  17 """Map CGI argument 'commands' to Image class method calls."""
  18
  19 import re
  20
  21 from google.appengine.api import images
  22
  23
  24 # VALID_TRANSFORMS lists valid parameters and simple regexes to test them.
  25 # The regexes only do very basic sanity checking, not full API validation.
  26 # The match groups are later used to pass the results on to the functions.
  27 VALID_TRANSFORMS = {
  28     u'crop': re.compile(','.join(['([01]\.[0-9]+)'] * 4)),
  29     u'horizontal_flip': re.compile('.*$'),
  30     u'im_feeling_lucky': re.compile('.*$'),
  31     u'resize': re.compile('([0-9]+),([0-9]+)$'),
  32     u'rotate': re.compile('(-?[0-9]+0)$'),
  33     u'vertical_flip': re.compile('.*$')
  34     }
  35
  36 # _CONVERSION_INFO lists functions to convert the string captured by the
  37 # regex into some other format which the API may require.
  38 _CONVERSION_INFO = {
  39     u'crop': float,
  40     u'resize': int,
  41     u'rotate': int
  42 }
  43
  44
  45 class ImageTransformer(object):
  46   """ImageTransformer: A wrapper for google.appengine.api.images.
  47
  48   In a sense, this is an inverse of google.appengine.api.images: it is
  49   intialized with image data to which multiple transforms are applied. This is
  50   initialized with a serialized list of transforms with can then be run on
  51   multiple images.
  52   """
  53
  54   def __init__(self, params, format):
  55     """Load and transform image data in a specified manner.
  56
  57     Args:
  58        params: UnicodeMultiDict of possible tranformations.
  59                Typically request.params from a web request.
  60                Unknown and invalid items will be mostly ignored.
  61        format: images.JPEG or images.PNG
  62     """
  63
  64     self.format = format
  65     self.transforms = []
  66     self.unknown_params = []
  67     self.invalid_params = []
  68     for (param, value) in params.iteritems():
  69       if param in VALID_TRANSFORMS:
  70         if VALID_TRANSFORMS[param].match(value):
  71           self.transforms.append((param, value))
  72         else:
  73           self.invalid_params.append(param)
  74       else:
  75         self.unknown_params.append(param)
  76
  77   def transform_image(self, image_data):
  78     """Applies this object's list of transforms to an image.
  79
  80     Args:
  81       image_data: binary image data in JPEG, PNG, or another format which the
  82                   images.image class can interpret.
  83
  84     Returns:
  85       Image data transformed using the transforms and formatting specified at
  86       ImageTransformer initialization time.
  87
  88     Raises:
  89       Any of the exceptions which images.Image.execute_transforms can raise.
  90
  91       images.BadRequestError when there is something wrong with the request
  92         specifications.
  93       images.NotImageError when the image data given is not an image.
  94       images.BadImageError when the image data given is corrupt.
  95       images.LargeImageError when the image data given is too large to process.
  96       images.TransformtionError when something errors during image manipulation.
  97       images.Error when something unknown, but bad, happens.
  98     """
  99
 100     image = images.Image(image_data)
 101     seen_transforms = set()
 102     for (transform, param) in self.transforms:
 103       if transform in seen_transforms:
 104         # we need to execture all transforms before continuing.
 105         image_data = image.execute_transforms(self.format)
 106         image = images.Image(image_data)
 107         seen_transforms.clear()
 108
 109       args = VALID_TRANSFORMS[transform].match(param).groups()
 110       if transform in _CONVERSION_INFO:
 111         args = [_CONVERSION_INFO[transform](arg) for arg in args]
 112       getattr(image, transform)(*args)
 113       seen_transforms.add(transform)
 114
 115     if seen_transforms:
 116       image_data = image.execute_transforms(self.format)
 117     return image_data