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A Python module to create and apply filters to images.

Project description

FImage

A Python module to apply and create multiples filters to images.

You need to be using Python 3.6 or greater to be able to use FImage.

Installation

pip install fimage

Example

A Simple filter

Create a file app.py with:

from fimage import FImage
from fimage.filters import Sepia


def main():
    # replace 'my_picture.jpg' with the path to your image
    image = FImage('my_picture.jpg')

    # apply the Sepia filter to the image
    image.apply(Sepia(90))

    # save the image with the applied filter
    image.save('my_picture_sepia.jpg')


if __name__ == "__main__":
    main()

Now, just run it :

python app.py

This is my_picture.jpg before the filter was applied

my_picture.jpg

And this is how new image my_picture_sepia.jpg looks like after the filter was applied

my_picture_sepia.jpg

Note: 90 represents the adjustment value we want to use for applying a sepia tone to this picture, lower values will result an image with less sepia tone while higher values will give us an image with a notorious sepia tone.

Most of the filters FImage offers will need an adjustment value to be passed.

Applying multiple filters

FImage offers more filters besides the Sepia one, even you can combine multiples filters to give a better look to your picture.

Modify the file app.py to import more filters from FImage

from fimage import FImage
from fimage.filters import Contrast, Brightness, Saturation


def main():
    image = FImage('my_picture.jpg')

    # apply the mutiple filters to the image
    image.apply(
        Saturation(20),
        Contrast(25),
        Brightness(15)
    )

    # save the image with the applied filter
    image.save('my_picture_mixed.jpg')


if __name__ == "__main__":
    main()

We run it by

python app.py

And our new my_picture_mixed.jpg looks like

my_picture_mixed.jpg

The order in which the filters are passed to the apply function matters, this is because the filters are applied in a sequential manner, so the next filter will be applied over the resultant image from the previous one.

Currently FImage supports the following filters:

  • FillColor
  • Sepia
  • Contrast
  • Brightness
  • Saturation
  • Vibrance
  • Grayscale
  • Hue
  • Colorize
  • Invert
  • Gamma
  • Noise
  • Clip
  • Exposure

Presets

Presets are just the combinations of multiple filters with already defined adjustment values.

Let’s change our app.py one more time to use the Presets

from fimage import FImage
from fimage.presets import SinCity


def main():
    # replace 'my_picture.jpg' with the path to your image
    image = FImage('my_picture.jpg')

    # apply the SinCity preset to the image
    image.apply(SinCity())

    # save the image with the applied preset
    image.save('my_picture_sincity.jpg')


if __name__ == "__main__":
    main()

After we run it, we get our new my_picture_sincity.jpg

my_picture_sincity.jpg

Currently supported Presets:

  • SinCity
  • OrangePeel
  • Love

Custom Presets

If you like the look your picture got after testing different filters and want to store this combination for applying it to more pictures, you can create your own Preset by just extending the Preset Class and specifying these filters and their adjust values in it.

In our app.py let’s do

from fimage import FImage
from fimage.presets import Preset
from fimage.filters import Contrast, Brightness, Saturation


# Create my custom preset and specify the filters to apply
class MyOwnPreset(Preset):
    transformations = [
        Contrast(30),
        Saturation(50),
        Brightness(10),
    ]


def main():
    # replace 'my_picture.jpg' with the path to your image
    image = FImage('my_picture.jpg')

    # apply MyOwnPreset to the image
    image.apply(MyOwnPreset())

    # save the image with the applied preset
    image.save('my_picture_custom.jpg')


if __name__ == "__main__":
    main()

The new my_picture_custom.jpg

my_picture_custom.jpg

Now, in this way MyOwnPreset has the combination of filters you like and you can use to modify more pictures.

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