Image augmentation library
Project description
Image augmentation library
This image augmentation library can be used to crop, flip, blur, sharpen, mix channels, overlay images. The main idea is to use only numpy library to perform these tasks. Augmented images can be used for Machine Learning projects
Getting it
To download augmentation_lib, either fork this github repo or simply use Pypi via pip.
$ pip install augmentation-lib
Features
This library performs different types of augmentation.
Crops:
center_crop_px
takes an image, width and height in pixels and returns center cropped image.
center_crop_percents
takes an image and size in percents (0 - 1) and returns center cropped image.
crop_px
takes an image starting point for cropping, width and height in pixels and returns cropped image.
crop_percents
takes an image starting point (height_coordinate, width_coordinate) in px, and size (height, width) in percents for cropping.
random_crop_px
takes a cropping size in pixels and randomly crops an image.
random_crop_percents
takes a cropping size in percents (0 - 1) and randomly crops an image.
Flips:
flip_horizontal
takes an image and flips it horizontally.
flip_vertical
takes an image and flips it vertically.
Padding:
zero_pad
takes an image and pads it with zeros by specified number of pixels.
Convolution:
conv_one_step
performs convolution for specified slice.
convolution_one_layer
performs one image layer convolution.
full_convolution
performs image convolution by specified kernel.
Dropouts:
dropout_random
performs random dropout of image pixels.
dropout
performs dropout of image pixels by specified intensity in percents (0 - 1).
Other augmentation:
shuffle
performs shuffle of image layers by specified order.
jitter
performs color jitter of one specified or random image layer. One of the color channels of the image is modified adding or subtracting a random and bounded value.
opacity
makes an image transparent.
opacity_object
makes an image background transparent, works better with object images.
overlay2_images
overlay 2 images with applied transparency.
resize_np
resize image using numpy and Nearest Neighbor Interpolation.
Showcase
More info about using this library you can find in: https://github.com/laume/augmentation_lib/blob/master/augmentation_lib/showcase.ipynb
Project details
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