Image Process Plugin 1.1.3 for Pelican Released

Image Process is a plugin for Pelican, a static site generator written in Python.

Image Process let you automate the processing of images based on their class attribute. Use this plugin to minimize the overall page weight and to save you a trip to Gimp or Photoshop each time you include an image in your post.

Image Process also makes it easy to create responsive images using the new HTML5 srcset attribute and <picture> tag. It does this by generating multiple derivative images from one or more sources.

Image Process will not overwrite your original images.

Image Process is used by this blog’s theme to resize the source images so they are the correct size for thumbnails on the main index page and the larger size they are displayed at on top of the articles.

This Release

This post is up because version 1.1.3 of the plugin has been released and posted PyPI. This version was released because version 1.1.2, as posted to PyPI, was broken; among other issues I couldn’t generated my blog!

To upgrade simply use pip:

pip install minchin.pelican.plugins.image_process --upgrade

The bulk of the README is included below as I haven’t posted it to the blog before. This plugin is a rather powerful, but as such is more involved to configure than many other Pelican plugins.

A special thanks to the team at Whisky Echo Bravo who developed the code of the plugin.

Installation

The easiest way to install Image Process is through the use of pip. This will also install the required dependencies automatically.

pip install minchin.pelican.plugins.image_process

Then, in your pelicanconf.py file, add Image Process to your list of plugins:

PLUGINS = [
            # ...
            'minchin.pelican.plugins.image_process',
            # ...
          ]

You will also need to configure your desired transformations (see Usage below) and add the appropriate class to images you want processed.

Requirements

Image Process requires Beautiful Soup, Pillow, Six, and Pelican. All these can be manually installed with pip:

pip install pillow beautifulsoup4 six pelican

If you encounter errors while processing JPEG files (on Linux), you may need to install the JPEG development library:

pip uninstall pillow
apt-get install libjpeg-dev
pip install pillow

Usage

Image Process scans your content for <img> tags with special classes. It then maps the classes to a set of image processing instructions, computes new images and modifies HTML code according to the instructions.

Define Transformations

The first step in using this module is to define some image transformations in your Pelican configuration file. Transformations are defined in the IMAGE_PROCESS dictionary, mapping a transformation name to a list of operations. There are three kinds of transformations: image replacement, responsive image and picture set.

Image replacement

The simplest image processing will replace the original image by a new, transformed image computed from the original. You may use this, for example, to ensure that all images are of the same size, or to compute a thumbnail from a larger image:

IMAGE_PROCESS = {
    'article-image': ["scale_in 300 300 True"],
    'thumb': ["crop 0 0 50% 50%", "scale_out 150 150 True", "crop 0 0 150 150"],
    }

These transformations tell Image process to transform the image referred by the src attribute of an <img> according to the list of operations specified and replace the src attribute by the URL of the transformed image.

For consistency with the other type of transformations described below, there is an alternative syntax for the processing instructions:

IMAGE_PROCESS = {
    'thumb': {'type': 'image',
              'ops': ["crop 0 0 50% 50%", "scale_out 150 150 True", "crop 0 0 150 150"],
              }
    'article-image': {'type': 'image',
                      'ops': ["scale_in 300 300 True"],
                      }
    }

To apply image replacement to the images in your articles, you must add them the special class image-process- followed by the name of the transformation you wish to apply. For example, let's pretend you have defined the transformation described above. If you write your content in HTML or in Markdown, do something like this:

<img class="image-process-article-image" src="/images/pelican.jpg"/>

In reStructuredText, use the :class: attribute of the image or the figure directive:

.. image:: /images/pelican.png
   :class: image-process-article-image

.. figure:: /images/pelican.png
   :class: image-process-article-image

Responsive Images

You can use Image process to automatically generate a set of images that will be selected for display by browsers according to the viewport width or according to the device resolution. To accomplish this, Image process will add a srcset attribute (and maybe a media and a sizes attribute) to the <img> tag.

Note that the srcset syntax is currently not supported by all browsers. However, browsers who do not support the srcset attribute will fall back to a default image specified by the still-present src attribute. See Can I Use for the current status on srcset support.

HTML5 supports two types of responsive image set. The first one is device-pixel-ratio-based, selecting higher resolution images for higher resolution devices; the second one is viewport-based, selecting images according to the viewport width. If you want to know more about HTML5 responsive images, I recommend this article for a gentle introduction to the srcset and <picture> syntaxes.

To tell Image process to generate a responsive image, add a responsive-image transformation to your your IMAGE_PROCESS dictionary, with the following syntax:

IMAGE_PROCESS = {
    'crisp': {'type': 'responsive-image',
              'srcset': [('1x', ["scale_in 800 600 True"]),
                         ('2x', ["scale_in 1600 1200 True"]),
                         ('4x', ["scale_in 3200 2400 True"]),
                         ],
               'default': '1x',
             },
    'large-photo': {'type': 'responsive-image',
                    'sizes': '(min-width: 1200px) 800px, (min-width: 992px) 650px, \
                              (min-width: 768px) 718px, 100vw',
                    'srcset': [('600w', ["scale_in 600 450 True"]),
                               ('800w', ["scale_in 800 600 True"]),
                               ('1600w', ["scale_in 1600 1200 True"]),
                               ],
                    'default': '800w',
                   },
    }

The crisp transformation is an example of a transformation enabling device-pixel-ratio-based selection. The srcset is a list of tuple, each tuple containing the image description ('1x', '2x', etc.) and the list of operations to generate the derivative image from the original image (the original image is the value of the src attribute of the <img>). Image descriptions are hints about the resolution of the associated image and must have the suffix x. The default names the image to use to replace the src attribute of the image. This is the image that will be displayed by browsers that do not support the srcset syntax.

The large-photo transformation is an example of a transformation enabling viewport-based selection. The sizes contains a rule to compute the width of the displayed image from the width of the viewport. Once the browser knows the image width, it will select an image source from the srcset. The srcset is a list of tuple, each tuple containing the image description ('600w', '800w', etc.) and the list of operations to generate the derivative image from the original image (the original image is the value of the src attribute of the <img>). Image descriptions are hints about the width in pixels of the associated image and must have the suffix w. The default names the image to use to replace the src attribute of the image. This is the image that will be displayed by browsers that do not support the srcset syntax.

In the two examples above, the default is a string referring to one of the images in the srcset. However, the default value could also be a list of operations to generate a different derivative image.

To make the images in your article responsive, you must add them the special class image-process- followed by the name of the transformation you wish to apply, exactly like you would do for the image replacement case, described above. So, if you write your content in HTML or in Markdown, do something like this:

<img class="image-process-large-photo" src="/images/pelican.jpg" />

In reStructuredText, use the :class: attribute of the image of the figure directive:

.. image:: /images/pelican.png
   :class: image-process-large-photo

.. figure:: /images/pelican.png
   :class: image-process-large-photo

Picture Sets

Image process can be use to generate the images used by a <picture> tag. The <picture> syntax allows for more flexibility in providing a choice of image to the browser. Again, if you want to know more about HTML5 responsive images, see this article for a gentle introduction to the srcset and <picture> syntaxes.

To tell Image process to generate the images for a <picture>, add a picture entry to your IMAGE_PROCESS dictionary with the following syntax:

IMAGE_PROCESS = {
  'example-pict': {'type': 'picture',
                   'sources': [{'name': 'default',
                                'media': '(min-width: 640px)',
                                'srcset': [('640w', ["scale_in 640 480 True"]),
                                           ('1024w', ["scale_in 1024 683 True"]),
                                           ('1600w', ["scale_in 1600 1200 True"]),
                                           ],
                                'sizes': '100vw',
                                },
                               {'name': 'source-1',
                                'srcset': [('1x', ["crop 100 100 200 200"]),
                                           ('2x', ["crop 100 100 300 300"]),
                                           ]
                                }
                               ],
                   'default': ('default', '640w'),
                   },
  }

Each of the sources entry is very similar to the responsive image describe above. Here, each source must have a name, which will be used to find the URL of the original image for this source in your article. The source may also have a media, which contains a rule used by the browser to select the active source. The default names the image to use to replace the src attribute of the <img> inside the <picture>. This is the image that will be displayed by browsers that do not support the <picture> syntax. In this example, it will use the image 640w from the source default. A list of operations could have been specified instead of 640w.

To generate a responsive <picture> for the images in your articles, you must add to your article a pseudo <picture> tag that looks like this:

<picture>
    <source class="source-1" src="/images/pelican-closeup.jpg"></source>
    <img class="image-process-example-pict" src="/images/pelican.jpg" />
</picture>

Each <source> tag maps a source name (the class attribute) to a file (the src attribute). The <img> must have the special class image-process- followed by the name of the transformation you wish to apply. The file referenced by the src attribute of the <img>> will be used as the special default source in your transformation definition.

The pseudo <picture> tag above can be used in articles written in HTML, Markdown or restructuredText. In reStructuredText, however, you can also use the figure directive to generate a <picture>. The figure image file will be used as the special default source; other sources must be added in the the legend section of the figure as image directives. The figure class must be image-process- followed by the name of the transformation you wish to apply, while the other images must have two classes: image-process and the name of the source they provide an image for:

.. figure:: /images/pelican.png
   :class: image-process-large-photo

    Test picture

    .. image:: /images/pelican-closeup.jpg
       :class: image-process source-1

The images in the legend section that are used as source for the <picture> will be removed from the image legend, so that they do not appear in your final article.

Transformations

Available operations for transformations are:

crop top left right bottom

Crop the image to the box (left, top)-(right, bottom). Values can be absolute (a number) or relative to the size of the image (a number followed by a percent sign %).

flip_horizontal

Flip the image horizontally.

flip_vertical

Flip the image vertically.

grayscale

Convert the image to grayscale.

resize width height

Resize the image. This operation does not preserve the image aspect ratio. Values can be absolute (a number) or relative to the size of the image (a number followed by a percent sign %).

rotate degree

Rotate the image.

scale_in width height upscale

Resize the image. This operation preserves the image aspect ratio and the resulting image will be no larger than width x height. Values can be absolute (a number) or relative to the size of the image (a number followed by a percent sign %). If upscale is False, smaller images will not be enlarged.

scale_out width height upscale

Resize the image. This operation preserves the image aspect ratio and the resulting image will be no smaller than width x height. Values can be absolute (a number) or relative to the size of the image (a number followed by a percent sign %). If upscale is False, smaller images will not be enlarged.

blur

Apply the pillow.ImageFilter.BLUR filter to the image.

contour

Apply the pillow.ImageFilter.CONTOUR filter to the image.

detail

Apply the pillow.ImageFilter.DETAIL filter to the image.

edge_enhance

Apply the pillow.ImageFilter.EDGE_ENHANCE filter to the image.

edge_enhance_more

Apply the pillow.ImageFilter.EDGE_ENHANCE_MORE filter to the image.

emboss

Apply the pillow.ImageFilter.EMBOSS filter to the image.

find_edges

Apply the pillow.ImageFilter.FIND_EDGES filter to the image.

smooth

Apply the pillow.ImageFilter.SMOOTH filter to the image.

smooth_more

Apply the pillow.ImageFilter.SMOOTH_MORE filter to the image.

sharpen

Apply the pillow.ImageFilter.SHARPEN filter to the image.

You can also define your own operations; the only requirement is that your operation should be a callable object expecting a pillow.Image as its first parameter and it should return the transformed image:

def crop_face(image):
    """Detect face in image and crop around it."""
    # TODO: Fancy algorithm.
    return image

IMAGE_PROCESS = {
    'face-thumbnail': [crop_face, "scale_out 150 150 True"]
    }

Additional Settings

Destination Directory

By default, the new images will be stored in a directory named derivative/<TRANSFORMATION_NAME> in the output folder at the same location as the original image. For example if the original image is located in the content/images folder. The computed images will be stored in the output/images/derivative/<TRANSFORMATION_NAME>. All the transformations are done in the output directory in order to avoid confusion with the source files or if we test multiple transformations. You can replace derivative by something else using the IMAGE_PROCESS_DIR setting in your Pelican configuration file:

IMAGE_PROCESS_DIR = 'derivees'

Force Image Processing

If the transformed image already exists and is newer than the original image, the plugin assumes that it should not recompute it again. You can force the plugin to recompute all images by setting IMAGE_PROCESS_FORCE to True in your Pelican configuration file.

IMAGE_PROCESS_FORCE = True

Selecting a HTML Parser

You may select the HTML parser which is used. The default is the builtin html.parser but you may also select html5lib or lxml by setting IMAGE_PROCESS_PARSER in your pelican configuration file , e.g.:

IMAGE_PROCESS_PARSER = "html5lib"

For details, refer to the BeautifulSoup documentation on parsers.

File Encoding

You may select a different file encoding to be used by BeautifulSoup as it opens your files. The default is uft-8.

IMAGE_PROCESS_ENCODING = "uft-8"

Known Issues

• Pillow, when resizing animated GIF files, does not return an animated file
• the setup.py file for this project does not run on Python 2.7. However, wheels of this project are "universal" and so can be generated by Python 3 and subsequently installed by Python 2.7.
• test require access to the pelican.tests module, which isn't included in the pelican distribution on PyPI.
• version 1.1.2, as uploaded to PyPI, is broken; use a different version. (see issue #2 for details)

Credits

Pelican image in test data by Jon Sullivan. Source: http://www.pdphoto.org/PictureDetail.php?mat=&pg=5726

Original Plugin developed by the team at Whisky Echo Bravo.