SubtleNoise#

class augraphy.augmentations.subtlenoise.SubtleNoise(subtle_range=10, p=1)[source]#

Bases: Augmentation

Emulates the imperfections in scanning solid colors due to subtle lighting differences.

Parameters:

subtle_range (int, optional) – The possible range of noise variation to sample from.
p (float, optional) – The probability that this Augmentation will be applied.

add_subtle_noise(image)[source]#

Generate mask of noise and add it to input image.

Parameters:: image (numpy.array (numpy.uint8)) – Image to apply the function.

Overview#

The Subtle Noise augmentation emulates the imperfections in scanning solid colors due to subtle lighting differences.

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 SubtleNoise augmentation instance is initialized and subtle range is set to 25.

Code example:

subtle_noise = SubtleNoise(subtle_range=25)

img_subtle_noise = subtle_noise(image)
cv2.imshow("subtle_noise", img_subtle_noise)

Augmented image: