TF Sprinkles
Sprinkles augmentation implemented in TensorFlow.
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Based on Less Wright's Medium article, Progessive Sprinkles: a New Data Augmentation for CNNs. See also his post on fast.ai.
To install:
pip install tf_sprinkles
To use:
from tf_sprinkles import Sprinkles
sprinkles = Sprinkles(num_holes, side_length)
Then call sprinkles(image) in the input pipeline for your image. A simple
example to get started using the cat.jpeg image located in the data folder
is:
import numpy as np
import tensorflow as tf
from tf_sprinkles import Sprinkles
from PIL import Image
from matplotlib import pyplot as plt
sprinkles = Sprinkles(num_holes=100, side_length=10)
img = Image.open('test/data/cat.jpeg')
img = np.asarray(img) / 255.
result = sprinkles(tf.constant(img, dtype=tf.float32))
plt.imshow(result.numpy())
Which results in the following image with sprinkles.
Note that the mode flag added in version 1.1.0 can be used to specify that
sprinkles should be filled with Gaussian noise (mode='gaussian'), randomly
filled with black or white (mode='salt_pepper'), or all black (the default
or mode=None).
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Release files for tf-sprinkles 1.1.3
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Release files / tf_sprinkles-1.1.3.tar.gz
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