variations 0.0.13

A simple interface that allows to process images.

variations

A simple interface that allows processing images.

Compatibility

• python >= 3.4

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 maximim width in pixels.This option have meaning only when corresponding value in size is zero
max_height	int	480	It specifies the maximim 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',
    )
)