+
−#!/usr/bin/env python
+
−#
+
−# Copyright 2007 Google Inc.
+
−#
+
−# Licensed under the Apache License, Version 2.0 (the "License");
+
−# you may not use this file except in compliance with the License.
+
−# You may obtain a copy of the License at
+
−#
+
−#     http://www.apache.org/licenses/LICENSE-2.0
+
−#
+
−# Unless required by applicable law or agreed to in writing, software
+
−# distributed under the License is distributed on an "AS IS" BASIS,
+
−# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+
−# See the License for the specific language governing permissions and
+
−# limitations under the License.
+
−#
+
−
+
−"""Stub version of the images API."""
+
−
+
−
+
−
+
−import logging
+
−import StringIO
+
−
+
−import PIL
+
−from PIL import _imaging
+
−from PIL import Image
+
−
+
−from google.appengine.api import apiproxy_stub
+
−from google.appengine.api import images
+
−from google.appengine.api.images import images_service_pb
+
−from google.appengine.runtime import apiproxy_errors
+
−
+
−
+
−class ImagesServiceStub(apiproxy_stub.APIProxyStub):
+
−  """Stub version of images API to be used with the dev_appserver."""
+
−
+
−  def __init__(self, service_name='images'):
+
−    """Preloads PIL to load all modules in the unhardened environment.
+
−
+
−    Args:
+
−      service_name: Service name expected for all calls.
+
−    """
+
−    super(ImagesServiceStub, self).__init__(service_name)
+
−    Image.init()
+
−
+
−  def _Dynamic_Transform(self, request, response):
+
−    """Trivial implementation of ImagesService::Transform.
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−
+
−    Based off documentation of the PIL library at
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−    http://www.pythonware.com/library/pil/handbook/index.htm
+
−
+
−    Args:
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−      request: ImagesTransformRequest, contains image request info.
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−      response: ImagesTransformResponse, contains transformed image.
+
−    """
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−    image = request.image().content()
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−    if not image:
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−      raise apiproxy_errors.ApplicationError(
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−          images_service_pb.ImagesServiceError.NOT_IMAGE)
+
−
+
−    image = StringIO.StringIO(image)
+
−    try:
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−      original_image = Image.open(image)
+
−    except IOError:
+
−      raise apiproxy_errors.ApplicationError(
+
−          images_service_pb.ImagesServiceError.BAD_IMAGE_DATA)
+
−
+
−    img_format = original_image.format
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−    if img_format not in ("BMP", "GIF", "ICO", "JPEG", "PNG", "TIFF"):
+
−      raise apiproxy_errors.ApplicationError(
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−          images_service_pb.ImagesServiceError.NOT_IMAGE)
+
−
+
−    new_image = self._ProcessTransforms(original_image,
+
−                                        request.transform_list())
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−
+
−    response_value = self._EncodeImage(new_image, request.output())
+
−    response.mutable_image().set_content(response_value)
+
−
+
−  def _EncodeImage(self, image, output_encoding):
+
−    """Encode the given image and return it in string form.
+
−
+
−    Args:
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−      image: PIL Image object, image to encode.
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−      output_encoding: ImagesTransformRequest.OutputSettings object.
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−
+
−    Returns:
+
−      str with encoded image information in given encoding format.
+
−    """
+
−    image_string = StringIO.StringIO()
+
−
+
−    image_encoding = "PNG"
+
−
+
−    if (output_encoding.mime_type() == images_service_pb.OutputSettings.JPEG):
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−      image_encoding = "JPEG"
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−
+
−      image = image.convert("RGB")
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−
+
−    image.save(image_string, image_encoding)
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−
+
−    return image_string.getvalue()
+
−
+
−  def _ValidateCropArg(self, arg):
+
−    """Check an argument for the Crop transform.
+
−
+
−    Args:
+
−      arg: float, argument to Crop transform to check.
+
−
+
−    Raises:
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−      apiproxy_errors.ApplicationError on problem with argument.
+
−    """
+
−    if not isinstance(arg, float):
+
−      raise apiproxy_errors.ApplicationError(
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−          images_service_pb.ImagesServiceError.BAD_TRANSFORM_DATA)
+
−
+
−    if not (0 <= arg <= 1.0):
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−      raise apiproxy_errors.ApplicationError(
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−          images_service_pb.ImagesServiceError.BAD_TRANSFORM_DATA)
+
−
+
−  def _CalculateNewDimensions(self,
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−                              current_width,
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−                              current_height,
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−                              req_width,
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−                              req_height):
+
−    """Get new resize dimensions keeping the current aspect ratio.
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−
+
−    This uses the more restricting of the two requested values to determine
+
−    the new ratio.
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−
+
−    Args:
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−      current_width: int, current width of the image.
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−      current_height: int, current height of the image.
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−      req_width: int, requested new width of the image.
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−      req_height: int, requested new height of the image.
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−
+
−    Returns:
+
−      tuple (width, height) which are both ints of the new ratio.
+
−    """
+
−
+
−    width_ratio = float(req_width) / current_width
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−    height_ratio = float(req_height) / current_height
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−
+
−    if req_width == 0 or (width_ratio > height_ratio and req_height != 0):
+
−      return int(height_ratio * current_width), req_height
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−    else:
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−      return req_width, int(width_ratio * current_height)
+
−
+
−  def _Resize(self, image, transform):
+
−    """Use PIL to resize the given image with the given transform.
+
−
+
−    Args:
+
−      image: PIL.Image.Image object to resize.
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−      transform: images_service_pb.Transform to use when resizing.
+
−
+
−    Returns:
+
−      PIL.Image.Image with transforms performed on it.
+
−
+
−    Raises:
+
−      BadRequestError if the resize data given is bad.
+
−    """
+
−    width = 0
+
−    height = 0
+
−
+
−    if transform.has_width():
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−      width = transform.width()
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−      if width < 0 or 4000 < width:
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−        raise apiproxy_errors.ApplicationError(
+
−            images_service_pb.ImagesServiceError.BAD_TRANSFORM_DATA)
+
−
+
−    if transform.has_height():
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−      height = transform.height()
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−      if height < 0 or 4000 < height:
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−        raise apiproxy_errors.ApplicationError(
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−            images_service_pb.ImagesServiceError.BAD_TRANSFORM_DATA)
+
−
+
−    current_width, current_height = image.size
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−    new_width, new_height = self._CalculateNewDimensions(current_width,
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−                                                         current_height,
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−                                                         width,
+
−                                                         height)
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−
+
−    return image.resize((new_width, new_height), Image.ANTIALIAS)
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−
+
−  def _Rotate(self, image, transform):
+
−    """Use PIL to rotate the given image with the given transform.
+
−
+
−    Args:
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−      image: PIL.Image.Image object to rotate.
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−      transform: images_service_pb.Transform to use when rotating.
+
−
+
−    Returns:
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−      PIL.Image.Image with transforms performed on it.
+
−
+
−    Raises:
+
−      BadRequestError if the rotate data given is bad.
+
−    """
+
−    degrees = transform.rotate()
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−    if degrees < 0 or degrees % 90 != 0:
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−      raise apiproxy_errors.ApplicationError(
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−          images_service_pb.ImagesServiceError.BAD_TRANSFORM_DATA)
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−    degrees %= 360
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−
+
−    degrees = 360 - degrees
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−    return image.rotate(degrees)
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−
+
−  def _Crop(self, image, transform):
+
−    """Use PIL to crop the given image with the given transform.
+
−
+
−    Args:
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−      image: PIL.Image.Image object to crop.
+
−      transform: images_service_pb.Transform to use when cropping.
+
−
+
−    Returns:
+
−      PIL.Image.Image with transforms performed on it.
+
−
+
−    Raises:
+
−      BadRequestError if the crop data given is bad.
+
−    """
+
−    left_x = 0.0
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−    top_y = 0.0
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−    right_x = 1.0
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−    bottom_y = 1.0
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−
+
−    if transform.has_crop_left_x():
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−      left_x = transform.crop_left_x()
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−      self._ValidateCropArg(left_x)
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−
+
−    if transform.has_crop_top_y():
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−      top_y = transform.crop_top_y()
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−      self._ValidateCropArg(top_y)
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−
+
−    if transform.has_crop_right_x():
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−      right_x = transform.crop_right_x()
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−      self._ValidateCropArg(right_x)
+
−
+
−    if transform.has_crop_bottom_y():
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−      bottom_y = transform.crop_bottom_y()
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−      self._ValidateCropArg(bottom_y)
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−
+
−    width, height = image.size
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−
+
−    box = (int(transform.crop_left_x() * width),
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−           int(transform.crop_top_y() * height),
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−           int(transform.crop_right_x() * width),
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−           int(transform.crop_bottom_y() * height))
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−
+
−    return image.crop(box)
+
−
+
−  def _CheckTransformCount(self, transform_map, req_transform):
+
−    """Check that the requested transform hasn't already been set in map.
+
−
+
−    Args:
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−      transform_map: {images_service_pb.ImagesServiceTransform: boolean}, map
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−        to use to determine if the requested transform has been called.
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−      req_transform: images_service_pb.ImagesServiceTransform, the requested
+
−        transform.
+
−
+
−    Raises:
+
−      BadRequestError if we are passed more than one of the same type of
+
−      transform.
+
−    """
+
−    if req_transform in transform_map:
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−      raise apiproxy_errors.ApplicationError(
+
−          images_service_pb.ImagesServiceError.BAD_TRANSFORM_DATA)
+
−    transform_map[req_transform] = True
+
−
+
−  def _ProcessTransforms(self, image, transforms):
+
−    """Execute PIL operations based on transform values.
+
−
+
−    Args:
+
−      image: PIL.Image.Image instance, image to manipulate.
+
−      trasnforms: list of ImagesTransformRequest.Transform objects.
+
−
+
−    Returns:
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−      PIL.Image.Image with transforms performed on it.
+
−
+
−    Raises:
+
−      BadRequestError if we are passed more than one of the same type of
+
−      transform.
+
−    """
+
−    new_image = image
+
−    transform_map = {}
+
−    for transform in transforms:
+
−      if transform.has_width() or transform.has_height():
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−        self._CheckTransformCount(
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−            transform_map,
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−            images_service_pb.ImagesServiceTransform.RESIZE
+
−        )
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−
+
−        new_image = self._Resize(new_image, transform)
+
−
+
−      elif transform.has_rotate():
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−        self._CheckTransformCount(
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−            transform_map,
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−            images_service_pb.ImagesServiceTransform.ROTATE
+
−        )
+
−
+
−        new_image = self._Rotate(new_image, transform)
+
−
+
−      elif transform.has_horizontal_flip():
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−        self._CheckTransformCount(
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−            transform_map,
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−            images_service_pb.ImagesServiceTransform.HORIZONTAL_FLIP
+
−        )
+
−
+
−        new_image = new_image.transpose(Image.FLIP_LEFT_RIGHT)
+
−
+
−      elif transform.has_vertical_flip():
+
−        self._CheckTransformCount(
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−            transform_map,
+
−            images_service_pb.ImagesServiceTransform.VERTICAL_FLIP
+
−        )
+
−
+
−        new_image = new_image.transpose(Image.FLIP_TOP_BOTTOM)
+
−
+
−      elif (transform.has_crop_left_x() or
+
−          transform.has_crop_top_y() or
+
−          transform.has_crop_right_x() or
+
−          transform.has_crop_bottom_y()):
+
−        self._CheckTransformCount(
+
−            transform_map,
+
−            images_service_pb.ImagesServiceTransform.CROP
+
−        )
+
−
+
−        new_image = self._Crop(new_image, transform)
+
−
+
−      elif transform.has_autolevels():
+
−        self._CheckTransformCount(
+
−            transform_map,
+
−            images_service_pb.ImagesServiceTransform.IM_FEELING_LUCKY
+
−        )
+
−        logging.info("I'm Feeling Lucky autolevels will be visible once this "
+
−                     "application is deployed.")
+
−      else:
+
−        logging.warn("Found no transformations found to perform.")
+
−
+
−    return new_image