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A simple interface that allows to process images.

Project description

variations

A simple interface that allows processing images.

Compatibility

  • python >= 3.5

Installation

  1. Run pip install variations

  2. (optional) If you want to use StackBlur

    pip install pillow-stackblur

  3. (optional) If you want to use Face Detection

    pip install face_recognition

Usage

    from PIL import Image
    from variations import processors
    from variations.variation import Variation
    from variations.utils import prepare_image

    variation = Variation(
        size=(400, 0),
        max_height=800,
        clip=False,
        upscale=False,
        anchor=processors.Anchor.TOP_LEFT,
        jpeg=dict(
            quality=92,
        ),
        webp=dict(
            lossless=True,
            quality=90,
        ),
        postprocessors=[
            processors.ColorOverlay('#FF0000', overlay_opacity=0.25),
        ],
    )

    img = Image.open('source.jpg')
    img = prepare_image(img, draft_size=variation.get_output_size(img.size))
    new_img = variation.process(img)
    dest_path = variation.replace_extension('dest.jpg')
    variation.save(new_img, dest_path)

Options

Type Examples Description
size tuple
list
(640, 480)
(640, 0)
The canvas size of image. If you set the width or height to zero, the corresponding value will be automatically adjusted based on the aspect ratio
max_width int 640 It specifies the maximum width in pixels.This option have meaning only when corresponding value in size is zero
max_height int 480 It specifies the maximum height in pixels.This option have meaning only when corresponding value in size is zero
clip bool When set to True, the image can be cropped when filling the canvas.
upscale bool When set to True, the image can be upscaled when filling the canvas.
anchor str
tuple
list
'tr' (top right)
'c' (center)
(1, 1) (bottom right)
Defines the anchor point.
face_detection bool Use a face detection system to find anchor point. You must install facial recognition api to use this.
format str 'JPEG' 'png' 'WebP' Enforce output image format. Defaults to 'AUTO', which means keep input format.
preprocessors list [processors.Crop(width=200, height=120, x=50, y=50)] PilKit processors are invoked before the main processing stage
postprocessors list [processors.ColorOverlay('#0000FF', 0.10)] PilKit processors are invoked after the main processing stage

Additional options for specific formats

It is possible to pass additional options to Image.save() method.

Variation(
    # ...
    jpeg=dict(
        quality=80,
        progressive=True,
    ),
    webp=dict(
        autoconvert=False,
        quality=80,
    ),
    tiff=dict(
        compression='tiff_jpeg',
    )
)

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