BrightnessTexturize

class augraphy.augmentations.brightnesstexturize.BrightnessTexturize(texturize_range=(0.8, 0.99), deviation=0.08, p=1)

Bases: Augmentation

Creates a random noise in the brightness channel to emulate paper textures.

Parameters:

• texturize_range – Pair of floats determining the range from which to sample values for the brightness matrix. Suggested value = <1.

• deviation (float, optional) – Additional variation for the uniform sample.

• p (float, optional) – The probability that this Augmentation will be applied.

Overview

The Brightness Texturize augmentation creates a random noise in the brightness channel to emulate paper textures.

Initially, a clean image with single line of text is created.

Code example:

# import libraries
import cv2
import numpy as np
from augraphy import *


# create a clean image with single line of text
image = np.full((500, 1500,3), 250, dtype="uint8")
cv2.putText(
    image,
    "Lorem ipsum dolor sit amet, consectetur adipiscing elit",
    (80, 250),
    cv2.FONT_HERSHEY_SIMPLEX,
    1.5,
    0,
    3,
)

cv2.imshow("Input image", image)

Clean image:

Example 1

In this example, a BrightnessTexturize augmentation instance is initialized and the texturize range is set to high value (0.9, 0.99. The deviation of adjusted texturization is set to 10% (0.1). Code example:

brightness_texturize = BrightnessTexturize(texturize_range=(0.9, 0.99),
                                           deviation=0.1 )

img_brightness_texturize = brightness_texturize(image)
cv2.imshow("brightness_texturize", img_brightness_texturize)

Augmented image: