App Engine provides the ability to manipulate image data using a dedicated Images service. The Images service can resize, rotate, flip, and crop images; it can composite multiple images into a single image; and it can convert image data between several formats. It can also enhance photographs using a predefined algorithm. The API can also provide information about an image, such as its format, width, height, and a histogram of color values.
The Images service can accept image data directly from the app, or it can use a Google Cloud Storage value. (The Images service can also use a Blobstore value, but we recommend the use of Cloud Storage instead.) When the source is Cloud Storage (or Blobstore), the size of the image to transform can be up to the maximum size of a Cloud Storage (or Blobstore) value. However, the transformed image is returned directly to the app, and so must be no larger than 32 megabytes. This is potentially useful for making thumbnail images of photographs uploaded to the Blobstore or Cloud Storage by users.
Transforming images in Python
The following example loads image data from the datastore, then uses the Images service to resize it and return it to the browser as a JPEG image.
from google.appengine.api import images from google.appengine.ext import ndb import webapp2 class Photo(ndb.Model): title = ndb.StringProperty() full_size_image = ndb.BlobProperty() class Thumbnailer(webapp2.RequestHandler): def get(self): if self.request.get("id"): photo = Photo.get_by_id(int(self.request.get("id"))) if photo: img = images.Image(photo.full_size_image) img.resize(width=80, height=100) img.im_feeling_lucky() thumbnail = img.execute_transforms(output_encoding=images.JPEG) self.response.headers['Content-Type'] = 'image/jpeg' self.response.out.write(thumbnail) return # Either "id" wasn't provided, or there was no image with that ID # in the datastore. self.error(404)
Available image transformations
The Images service can resize, rotate, flip, and crop images, and enhance photographs. It can also composite multiple images into a single image.
You can resize the image while maintaining the same aspect ratio. Neither the width nor the height of the resized image can exceed 4000 pixels.
You can rotate the image in 90 degree increments.
You can flip the image horizontally.
You can flip the image vertically.
You can crop the image with a given bounding box.
I'm Feeling Lucky
The "I'm Feeling Lucky" transform enhances dark and bright colors in an image and adjusts both color and contrast to optimal levels.
The service accepts image data in the JPEG, PNG, WEBP, GIF (including animated GIF), BMP, TIFF and ICO formats.
It can return transformed images in the JPEG, WEBP and PNG formats. If the input format and the output format are different, the service converts the input data to the output format before performing the transformation.
- Using the Image() class allows you to perform simple image transformations, such as crop, flip, and rotate.
- Using get_serving_url() allows you to dynamically resize and crop images, so you don't need to store different image sizes on the server. This method returns a URL that serves the image, and transformations to the image are encoded in this URL.
Using the Image() Class
You can transform images from Cloud Storage or Blobstore as long as the image size is smaller than the maximum Cloud Storage or Blobstore value size. Note, however, that the result of the transformation is returned directly to the app, and must therefore not exceed the API response limit of 32 megabytes. You can use this to make thumbnail images of photographs uploaded by users.
To transform an image from Cloud Storage or Blobstore in Python, instead of setting the
image_data argument of the Image constructor with the image data, set the
blob_key argument to the Blobstore key whose value is the image. The rest of the API behaves as expected. The
execute_transforms() method returns the result of the transforms, or throws an
LargeImageError if the result is larger than the maximum size of 32 megabytes.
from google.appengine.api import images from google.appengine.ext import blobstore import webapp2 class Thumbnailer(webapp2.RequestHandler): def get(self): blob_key = self.request.get("blob_key") if blob_key: blob_info = blobstore.get(blob_key) if blob_info: img = images.Image(blob_key=blob_key) img.resize(width=80, height=100) img.im_feeling_lucky() thumbnail = img.execute_transforms(output_encoding=images.JPEG) self.response.headers['Content-Type'] = 'image/jpeg' self.response.out.write(thumbnail) return # Either "blob_key" wasn't provided, or there was no value with that ID # in the Blobstore. self.error(404)
Using get_serving_url()In addition to the Images API, you can also use the transforms provided in the Python Imaging Library (PIL) in your Python 2.7 app. To do this, declare the library in the libraries section of the
app.yamlfile. However, if you wish to use PIL in your local environment (using the development server) you must also download and install PIL or pillow locally.
The get_serving_url() method allows you to generate a fixed, dedicated URL for an image that is stored in Cloud Storage or Blobstore.
The generated URL uses highly-optimized image serving infrastructure that is separate from your application. Because it's served separately the serving URL does not incur any dynamic load on your application which can be very cost effective. The URL returned by this method is always publicly accessable but not guessable.
If you wish to stop serving the URL, delete it using the delete_serving_url() function.
The method returns a URL encoded with the specified size and crop arguments. If you do not specify any arguments, the method returns the default URL for the image, for example:
You can resize and crop the image dynamically by specifying the arguments in the URL. The available arguments are:
xxis an integer from 0–1600 representing the length, in pixels, of the image's longest side. For example, adding
=s32resizes the image so its longest dimension is 32 pixels.
=sxx-cwhere xx is an integer from 0–1600 representing the cropped image size in pixels, and
-ctells the system to crop the image.
# Resize the image to 32 pixels (aspect-ratio preserved) http://lhx.ggpht.com/randomStringImageId=s32 # Crop the image to 32 pixels http://lhx.ggpht.com/randomStringImageId=s32-c
Images and the development server
The development server uses your local machine to perform the capabilities of the Images service.
The Python development server uses the Python Imaging Library (PIL) to simulate the Image service. This library is not included with the Python standard library or the SDK, and must be installed separately. The pillow fork also works. The WEBP image format is only supported if a suitable PIL decoder plugin has been installed.
A note about deletion
Whether you store your images in Cloud Storage or Blobstore, the right way to stop an image from being publicly accessible through the serving URL is to call the delete_serving_url() function.
If you merely delete the underlying stored image from Cloud Storage or Blobstore, under some circumstances the image may remain accessible through the serving URL.
Serving URLs will stop working if the application that created them is disabled or deleted, even if the underlying image remains available.
Quotas, limits, and pricing
There is currently no additional charge incurred by using the Images API. See the App Engine pricing page.
Each Images service request counts toward the Image Manipulation API Calls quota. An app can perform multiple transformations of an image in a single API call.
Data sent to the Images service counts toward the Data Sent to (Images) API quota. Data received from the Images service counts toward the Data Received from (Images) API quota.
Each transformation of an image counts toward the Transformations Executed quota.
In addition to quotas, the following limits apply to the use of the Images service:
|maximum data size of image sent to service||32 megabytes|
|maximum data size of image received from service||32 megabytes|
|maximum size of image sent or received from service||50 megapixels|