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https://github.com/matthewwithanm/django-imagekit

Automated image processing for Django. Currently v4.0
https://github.com/matthewwithanm/django-imagekit

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Automated image processing for Django. Currently v4.0

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README 

        
|Build Status|_



.. |Build Status| image:: https://github.com/matthewwithanm/django-imagekit/actions/workflows/python.yml/badge.svg?branch=develop

.. _Build Status: https://github.com/matthewwithanm/django-imagekit/actions/workflows/python.yml



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 programmatically 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 `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``



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



Usage Overview

==============



.. _specs:



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



    



(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



    



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 %}

    Click to download a cool {{ th.width }} x {{ th.height }} image!



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  tag:



.. code-block:: html



    



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 `_

to report bugs with django-imagekit. `A mailing list `_

also exists to discuss the project and ask questions, as well as the official

`#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

.. _`contributing guidelines`: https://github.com/matthewwithanm/django-imagekit/blob/develop/CONTRIBUTING.rst