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 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.
The easiest way to install Image Process is via Pip. This will also install the required dependencies automatically.
python -m pip install pelican-image-processYou will then need to configure your desired transformations (see Usage below) and add the appropriate class to images you want processed.
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.
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.
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 to by the src attribute of an <img> according to the
list of operations specified, and replace the src attribute with the
URL of the transformed image.
For consistency with other types 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 to them
the special class image-process-<transform>, in which <transform> is the ID
of the transformation you wish to apply.
Let's say you have defined the transformation described above. To get your image processed, it needs to have the right CSS class:
<img class="image-process-article-image" src="/images/pelican.jpg"/>This can be produced in Markdown with:
{: .image-process-article-image}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-imageThe reStructuredText reader will convert underscores (
_) to dashes (-) in class names. To make sure everything runs smoothly, do not use underscores in your transformation names.
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.
HTML5 supports two types of responsive image sets. 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 size. You can read more about
HTML5 responsive images 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 tuples, 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 setting specifies 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 setting specifies 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 setting 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 to them the
special class image-process-<transform>, in which <transform> is the ID of the
transformation you wish to apply, exactly like you would do for the
image replacement case, described above.
So, in HTML it should look like this:
<img class="image-process-large-photo" src="/images/pelican.jpg"/>Which can be produced in Markdown with:
{: .image-process-large-photo}In reStructuredText, use the :class: attribute of the image or
the figure directive:
.. image:: /images/pelican.jpg
:class: image-process-large-photo.. figure:: /images/pelican.jpg
:class: image-process-large-photoImage Process can be used 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, you can read more about HTML5 responsive images 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 entries 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
setting specifies 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.
You can't produce this with pure Markdown and must instead resort to raw HTML.
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 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.jpg
:class: image-process-example-pict
Test picture
.. image:: /images/pelican-closeup.jpg
:class: image-process source-1The 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.
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 <degrees>: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>isFalse, 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>isFalse, smaller images will not be enlarged. -
blur:Apply the
pillow.ImageFilter.BLURfilter to the image. -
contour:Apply the
pillow.ImageFilter.CONTOURfilter to the image. -
detail:Apply the
pillow.ImageFilter.DETAILfilter to the image. -
edge_enhance:Apply the
pillow.ImageFilter.EDGE_ENHANCEfilter to the image. -
edge_enhance_more:Apply the
pillow.ImageFilter.EDGE_ENHANCE_MOREfilter to the image. -
emboss:Apply the
pillow.ImageFilter.EMBOSSfilter to the image. -
find_edges:Apply the
pillow.ImageFilter.FIND_EDGESfilter to the image. -
smooth:Apply the
pillow.ImageFilter.SMOOTH filterto the image. -
smooth_more:Apply the
pillow.ImageFilter.SMOOTH_MOREfilter to the image. -
sharpen:Apply the
pillow.ImageFilter.SHARPENfilter 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."""
# Fancy algorithm.
return image
IMAGE_PROCESS = {
"face-thumbnail": [crop_face, "scale_out 150 150 True"]
}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 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 settings file:
IMAGE_PROCESS_DIR = "derivees"If the transformed image already exists and is newer than the original
image, the plugin assumes that it should not re-compute it again. You
can force the plugin to re-compute all images by setting
IMAGE_PROCESS_FORCE to True in your Pelican configuration file.
IMAGE_PROCESS_FORCE = TrueYou may select the HTML parser which is used. The default is the built-in
html.parser but you may also select html5lib or lxml by setting
IMAGE_PROCESS_PARSER in your Pelican settings file. For example:
IMAGE_PROCESS_PARSER = "html5lib"For details, refer to the BeautifulSoup documentation on parsers.
You may select a different file encoding to be used by BeautifulSoup as it
opens your files. The default is utf-8.
IMAGE_PROCESS_ENCODING = "utf-8"You may ask Image Process to copy the EXIF tags from your original image to the transformed images. You must have exiftool installed.
IMAGE_PROCESS_COPY_EXIF_TAGS = True- Pillow, when resizing animated GIF files, does not return an animated file.
Contributions are welcome and much appreciated. Every little bit helps. You can contribute by improving the documentation, adding missing features, and fixing bugs. You can also help out by reviewing and commenting on existing issues.
To start contributing to this plugin, review the Contributing to Pelican documentation, beginning with the Contributing Code section.
If you need to regenerate the transformed images used by the test suite, there is a helper function to do this for you. From the Python REPL:
>>> from pelican.plugins.image_process.test_image_process import generate_test_images
>>> generate_test_images()
36 test images generated!This project is licensed under the AGPL-3.0 license.
Pelican image in test data by Jon Sullivan. Published under a Creative Commons Public Domain license.