tf-sprinkles 1.1.0

A fast and efficient implimentation of progressive sprinkles augmentation.

tf_sprinkles

Sprinkles augmentation implemented in TensorFlow

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('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).