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|Build Status|_

.. _Build Status: https://travis-ci.org/matthewwithanm/django-imagekit

ImageKit is a Django app for processing images. Need a thumbnail? A
black-and-white version of a user-uploaded image? ImageKit will make them for
you. If you need to programatically generate one image from another, you need
ImageKit.

ImageKit comes with a bunch of image processors for common tasks like resizing
and cropping, but you can also create your own. For an idea of what's possible,
check out the `Instakit`__ project.

**For the complete documentation on the latest stable version of ImageKit, see**
`ImageKit on RTD`_.

.. _`ImageKit on RTD`: http://django-imagekit.readthedocs.org
__ https://github.com/fish2000/instakit


Installation
============

1. Install `PIL`_ or `Pillow`_. (If you're using an ``ImageField`` in Django,
   you should have already done this.)
2. ``pip install django-imagekit``
3. Add ``'imagekit'`` to your ``INSTALLED_APPS`` list in your project's settings.py

.. note:: If you've never seen Pillow before, it considers itself a
   more-frequently updated "friendly" fork of PIL that's compatible with
   setuptools. As such, it shares the same namespace as PIL does and is a
   drop-in replacement.

.. _`PIL`: http://pypi.python.org/pypi/PIL
.. _`Pillow`: http://pypi.python.org/pypi/Pillow


Usage Overview
==============


Specs
-----

You have one image and you want to do something to it to create another image.
But how do you tell ImageKit what to do? By defining an image spec.

An **image spec** is a type of **image generator** that generates a new image
from a source image.


Defining Specs In Models
^^^^^^^^^^^^^^^^^^^^^^^^

The easiest way to use define an image spec is by using an ImageSpecField on
your model class:

.. code-block:: python

    from django.db import models
    from imagekit.models import ImageSpecField
    from imagekit.processors import ResizeToFill

    class Profile(models.Model):
        avatar = models.ImageField(upload_to='avatars')
        avatar_thumbnail = ImageSpecField(source='avatar',
                                          processors=[ResizeToFill(100, 50)],
                                          format='JPEG',
                                          options={'quality': 60})

    profile = Profile.objects.all()[0]
    print(profile.avatar_thumbnail.url)    # > /media/CACHE/images/982d5af84cddddfd0fbf70892b4431e4.jpg
    print(profile.avatar_thumbnail.width)  # > 100

As you can probably tell, ImageSpecFields work a lot like Django's
ImageFields. The difference is that they're automatically generated by
ImageKit based on the instructions you give. In the example above, the avatar
thumbnail is a resized version of the avatar image, saved as a JPEG with a
quality of 60.

Sometimes, however, you don't need to keep the original image (the avatar in
the above example); when the user uploads an image, you just want to process it
and save the result. In those cases, you can use the ``ProcessedImageField``
class:

.. code-block:: python

    from django.db import models
    from imagekit.models import ProcessedImageField
    from imagekit.processors import ResizeToFill

    class Profile(models.Model):
        avatar_thumbnail = ProcessedImageField(upload_to='avatars',
                                               processors=[ResizeToFill(100, 50)],
                                               format='JPEG',
                                               options={'quality': 60})

    profile = Profile.objects.all()[0]
    print(profile.avatar_thumbnail.url)    # > /media/avatars/MY-avatar.jpg
    print(profile.avatar_thumbnail.width)  # > 100

This is pretty similar to our previous example. We don't need to specify a
"source" any more since we're not processing another image field, but we do need
to pass an "upload_to" argument. This behaves exactly as it does for Django
ImageFields.

.. note::

    You might be wondering why we didn't need an "upload_to" argument for our
    ImageSpecField. The reason is that ProcessedImageFields really are just like
    ImageFields—they save the file path in the database and you need to run
    syncdb (or create a migration) when you add one to your model.

    ImageSpecFields, on the other hand, are virtual—they add no fields to your
    database and don't require a database. This is handy for a lot of reasons,
    but it means that the path to the image file needs to be programmatically
    constructed based on the source image and the spec.


Defining Specs Outside of Models
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Defining specs as models fields is one very convenient way to process images,
but it isn't the only way. Sometimes you can't (or don't want to) add fields to
your models, and that's okay. You can define image spec classes and use them
directly. This can be especially useful for doing image processing in views—
particularly when the processing being done depends on user input.

.. code-block:: python

    from imagekit import ImageSpec
    from imagekit.processors import ResizeToFill

    class Thumbnail(ImageSpec):
        processors = [ResizeToFill(100, 50)]
        format = 'JPEG'
        options = {'quality': 60}

It's probably not surprising that this class is capable of processing an image
in the exact same way as our ImageSpecField above. However, unlike with the
image spec model field, this class doesn't define what source the spec is acting
on, or what should be done with the result; that's up to you:

.. code-block:: python

    source_file = open('/path/to/myimage.jpg', 'rb')
    image_generator = Thumbnail(source=source_file)
    result = image_generator.generate()

.. note::

    You don't have to use ``open``! You can use whatever File-like object you
    want—including a model's ``ImageField``.

The result of calling ``generate()`` on an image spec is a file-like object
containing our resized image, with which you can do whatever you want. For
example, if you wanted to save it to disk:

.. code-block:: python

    dest = open('/path/to/dest.jpg', 'wb')
    dest.write(result.read())
    dest.close()


Using Specs In Templates
^^^^^^^^^^^^^^^^^^^^^^^^

If you have a model with an ImageSpecField or ProcessedImageField, you can
easily use those processed image just as you would a normal image field:

.. code-block:: html

    <img src="{{ profile.avatar_thumbnail.url }}" />

(This is assuming you have a view that's setting a context variable named
"profile" to an instance of our Profile model.)

But you can also generate processed image files directly in your template—from
any image—without adding anything to your model. In order to do this, you'll
first have to define an image generator class (remember, specs are a type of
generator) in your app somewhere, just as we did in the last section. You'll
also need a way of referring to the generator in your template, so you'll need
to register it.

.. code-block:: python

    from imagekit import ImageSpec, register
    from imagekit.processors import ResizeToFill

    class Thumbnail(ImageSpec):
        processors = [ResizeToFill(100, 50)]
        format = 'JPEG'
        options = {'quality': 60}

    register.generator('myapp:thumbnail', Thumbnail)

.. note::

    You can register your generator with any id you want, but choose wisely!
    If you pick something too generic, you could have a conflict with another
    third-party app you're using. For this reason, it's a good idea to prefix
    your generator ids with the name of your app. Also, ImageKit recognizes
    colons as separators when doing pattern matching (e.g. in the generateimages
    management command), so it's a good idea to use those too!

.. warning::

    This code can go in any file you want—but you need to make sure it's loaded!
    In order to keep things simple, ImageKit will automatically try to load an
    module named "imagegenerators" in each of your installed apps. So why don't
    you just save yourself the headache and put your image specs in there?

Now that we've created an image generator class and registered it with ImageKit,
we can use it in our templates!


generateimage
"""""""""""""

The most generic template tag that ImageKit gives you is called "generateimage".
It requires at least one argument: the id of a registered image generator.
Additional keyword-style arguments are passed to the registered generator class.
As we saw above, image spec constructors expect a source keyword argument, so
that's what we need to pass to use our thumbnail spec:

.. code-block:: html

    {% load imagekit %}

    {% generateimage 'myapp:thumbnail' source=source_file %}

This will output the following HTML:

.. code-block:: html

    <img src="/media/CACHE/images/982d5af84cddddfd0fbf70892b4431e4.jpg" width="100" height="50" />

You can also add additional HTML attributes; just separate them from your
keyword args using two dashes:

.. code-block:: html

    {% load imagekit %}

    {% generateimage 'myapp:thumbnail' source=source_file -- alt="A picture of Me" id="mypicture" %}

Not generating HTML image tags? No problem. The tag also functions as an
assignment tag, providing access to the underlying file object:

.. code-block:: html

    {% load imagekit %}

    {% generateimage 'myapp:thumbnail' source=source_file as th %}
    <a href="{{ th.url }}">Click to download a cool {{ th.width }} x {{ th.height }} image!</a>


thumbnail
"""""""""

Because it's such a common use case, ImageKit also provides a "thumbnail"
template tag:

.. code-block:: html

    {% load imagekit %}

    {% thumbnail '100x50' source_file %}

Like the generateimage tag, the thumbnail tag outputs an <img> tag:

.. code-block:: html

    <img src="/media/CACHE/images/982d5af84cddddfd0fbf70892b4431e4.jpg" width="100" height="50" />

Comparing this syntax to the generateimage tag above, you'll notice a few
differences.

First, we didn't have to specify an image generator id; unless we tell it
otherwise, thumbnail tag uses the generator registered with the id
"imagekit:thumbnail". **It's important to note that this tag is *not* using the
Thumbnail spec class we defined earlier**; it's using the generator registered
with the id "imagekit:thumbnail" which, by default, is
``imagekit.generatorlibrary.Thumbnail``.

Second, we're passing two positional arguments (the dimensions and the source
image) as opposed to the keyword arguments we used with the generateimage tag.

Like with the generateimage tag, you can also specify additional HTML attributes
for the thumbnail tag, or use it as an assignment tag:

.. code-block:: html

    {% load imagekit %}

    {% thumbnail '100x50' source_file -- alt="A picture of Me" id="mypicture" %}
    {% thumbnail '100x50' source_file as th %}


Using Specs in Forms
^^^^^^^^^^^^^^^^^^^^

In addition to the model field above, there's also a form field version of the
``ProcessedImageField`` class. The functionality is basically the same (it
processes an image once and saves the result), but it's used in a form class:

.. code-block:: python

    from django import forms
    from imagekit.forms import ProcessedImageField
    from imagekit.processors import ResizeToFill

    class ProfileForm(forms.Form):
        avatar_thumbnail = ProcessedImageField(spec_id='myapp:profile:avatar_thumbnail',
                                               processors=[ResizeToFill(100, 50)],
                                               format='JPEG',
                                               options={'quality': 60})

The benefit of using ``imagekit.forms.ProcessedImageField`` (as opposed to
``imagekit.models.ProcessedImageField`` above) is that it keeps the logic for
creating the image outside of your model (in which you would use a normal Django
ImageField). You can even create multiple forms, each with their own
ProcessedImageField, that all store their results in the same image field.


Processors
----------

So far, we've only seen one processor: ``imagekit.processors.ResizeToFill``. But
ImageKit is capable of far more than just resizing images, and that power comes
from its processors.

Processors take a PIL image object, do something to it, and return a new one.
A spec can make use of as many processors as you'd like, which will all be run
in order.

.. code-block:: python

    from imagekit import ImageSpec
    from imagekit.processors import TrimBorderColor, Adjust

    class MySpec(ImageSpec):
        processors = [
            TrimBorderColor(),
            Adjust(contrast=1.2, sharpness=1.1),
        ]
        format = 'JPEG'
        options = {'quality': 60}

The ``imagekit.processors`` module contains processors for many common
image manipulations, like resizing, rotating, and color adjustments. However,
if they aren't up to the task, you can create your own. All you have to do is
define a class that implements a ``process()`` method:

.. code-block:: python

    class Watermark(object):
        def process(self, image):
            # Code for adding the watermark goes here.
            return image

That's all there is to it! To use your fancy new custom processor, just include
it in your spec's ``processors`` list:

.. code-block:: python

    from imagekit import ImageSpec
    from imagekit.processors import TrimBorderColor, Adjust
    from myapp.processors import Watermark

    class MySpec(ImageSpec):
        processors = [
            TrimBorderColor(),
            Adjust(contrast=1.2, sharpness=1.1),
            Watermark(),
        ]
        format = 'JPEG'
        options = {'quality': 60}

Note that when you import a processor from ``imagekit.processors``, imagekit
in turn imports the processor from `PILKit`_. So if you are looking for
available processors, look at PILKit.

.. _`PILKit`: https://github.com/matthewwithanm/pilkit


Admin
-----

ImageKit also contains a class named ``imagekit.admin.AdminThumbnail``
for displaying specs (or even regular ImageFields) in the
`Django admin change list`_. AdminThumbnail is used as a property on
Django admin classes:

.. code-block:: python

    from django.contrib import admin
    from imagekit.admin import AdminThumbnail
    from .models import Photo

    class PhotoAdmin(admin.ModelAdmin):
        list_display = ('__str__', 'admin_thumbnail')
        admin_thumbnail = AdminThumbnail(image_field='thumbnail')

    admin.site.register(Photo, PhotoAdmin)

To use specs defined outside of models:

.. code-block:: python
    
    from django.contrib import admin
    from imagekit.admin import AdminThumbnail
    from imagekit import ImageSpec
    from imagekit.processors import ResizeToFill
    from imagekit.cachefiles import ImageCacheFile

    from .models import Photo

    class AdminThumbnailSpec(ImageSpec):
        processors = [ResizeToFill(100, 30)]
        format = 'JPEG'
        options = {'quality': 60 }

    def cached_admin_thumb(instance):
        # `image` is the name of the image field on the model
        cached = ImageCacheFile(AdminThumbnailSpec(instance.image))
        # only generates the first time, subsequent calls use cache
        cached.generate()
        return cached

    class PhotoAdmin(admin.ModelAdmin):
        list_display = ('__str__', 'admin_thumbnail')
        admin_thumbnail = AdminThumbnail(image_field=cached_admin_thumb)

    admin.site.register(Photo, PhotoAdmin)

 
AdminThumbnail can even use a custom template. For more information, see
``imagekit.admin.AdminThumbnail``.

.. _`Django admin change list`: https://docs.djangoproject.com/en/dev/intro/tutorial02/#customize-the-admin-change-list


Management Commands
-------------------

ImageKit has one management command—`generateimages`—which will generate cache
files for all of your registered image generators. You can also pass it a list
of generator ids in order to generate images selectively.


Community
=========

Please use `the GitHub issue tracker <https://github.com/matthewwithanm/django-imagekit/issues>`_
to report bugs with django-imagekit. `A mailing list <https://groups.google.com/forum/#!forum/django-imagekit>`_
also exists to discuss the project and ask questions, as well as the official
`#imagekit <irc://irc.freenode.net/imagekit>`_ channel on Freenode.


Contributing
============

We love contributions! And you don't have to be an expert with the library—or
even Django—to contribute either: ImageKit's processors are standalone classes
that are completely separate from the more intimidating internals of Django's
ORM. If you've written a processor that you think might be useful to other
people, open a pull request so we can take a look!

You can also check out our list of `open, contributor-friendly issues`__ for
ideas.

Check out our `contributing guidelines`__ for more information about pitching in
with ImageKit.


__ https://github.com/matthewwithanm/django-imagekit/issues?labels=contributor-friendly&state=open
__ https://github.com/matthewwithanm/django-imagekit/blob/develop/CONTRIBUTING.rst