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| import imgaug as ia | |
| from imgaug import augmenters as iaa | |
| # Sometimes(0.5, ...) applies the given augmenter in 50% of all cases, | |
| # e.g. Sometimes(0.5, GaussianBlur(0.3)) would blur roughly every second image. | |
| sometimes = lambda aug: iaa.Sometimes(0.2, aug) | |
| # Define our sequence of augmentation steps that will be applied to every image | |
| # All augmenters with per_channel=0.5 will sample one value _per image_ | |
| # in 50% of all cases. In all other cases they will sample new values | |
| # _per channel_. | |
| HUGE = sometimes(iaa.Sequential( | |
| [ | |
| # apply the following augmenters to most images | |
| sometimes(iaa.Cartoon()), | |
| # crop images by -5% to 10% of their height/width | |
| sometimes(iaa.CropAndPad( | |
| percent=(-0.05, 0.1), | |
| pad_mode=ia.ALL, | |
| pad_cval=(0, 255) | |
| )), | |
| sometimes(iaa.Affine( | |
| scale={"x": (0.8, 1.2), "y": (0.8, 1.2)}, # scale images to 80-120% of their size, individually per axis | |
| translate_percent={"x": (-0.2, 0.2), "y": (-0.2, 0.2)}, # translate by -20 to +20 percent (per axis) | |
| rotate=(-45, 45), # rotate by -45 to +45 degrees | |
| shear=(-16, 16), # shear by -16 to +16 degrees | |
| order=[0, 1], # use nearest neighbour or bilinear interpolation (fast) | |
| cval=(0, 255), # if mode is constant, use a cval between 0 and 255 | |
| mode=ia.ALL # use any of scikit-image's warping modes (see 2nd image from the top for examples) | |
| )), | |
| # execute 0 to 5 of the following (less important) augmenters per image | |
| # don't execute all of them, as that would often be way too strong | |
| iaa.SomeOf((0, 5), | |
| [ | |
| sometimes(iaa.Superpixels(p_replace=(0, 1.0), n_segments=(20, 200))), # convert images into their superpixel representation | |
| iaa.OneOf([ | |
| iaa.GaussianBlur((0, 3.0)), # blur images with a sigma between 0 and 3.0 | |
| iaa.AverageBlur(k=(2, 7)), # blur image using local means with kernel sizes between 2 and 7 | |
| iaa.MedianBlur(k=(3, 11)), # blur image using local medians with kernel sizes between 2 and 7 | |
| ]), | |
| iaa.Sharpen(alpha=(0, 1.0), lightness=(0.75, 1.5)), # sharpen images | |
| iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0)), # emboss images | |
| # search either for all edges or for directed edges, | |
| # blend the result with the original image using a blobby mask | |
| iaa.SimplexNoiseAlpha(iaa.OneOf([ | |
| iaa.EdgeDetect(alpha=(0.5, 1.0)), | |
| iaa.DirectedEdgeDetect(alpha=(0.5, 1.0), direction=(0.0, 1.0)), | |
| ])), | |
| iaa.AdditiveGaussianNoise(loc=0, scale=(0.0, 0.05*255), per_channel=0.5), # add gaussian noise to images | |
| iaa.OneOf([ | |
| iaa.Dropout((0.01, 0.1), per_channel=0.5), # randomly remove up to 10% of the pixels | |
| iaa.CoarseDropout((0.03, 0.15), size_percent=(0.02, 0.05), per_channel=0.2), | |
| ]), | |
| # iaa.Invert(0.05, per_channel=True), # invert color channels | |
| iaa.Add((-10, 10), per_channel=0.5), # change brightness of images (by -10 to 10 of original value) | |
| iaa.AddToHueAndSaturation((-20, 20)), # change hue and saturation | |
| # either change the brightness of the whole image (sometimes | |
| # per channel) or change the brightness of subareas | |
| iaa.OneOf([ | |
| iaa.Multiply((0.5, 1.5), per_channel=0.5), | |
| iaa.FrequencyNoiseAlpha( | |
| exponent=(-4, 0), | |
| first=iaa.Multiply((0.5, 1.5), per_channel=True), | |
| second=iaa.LinearContrast((0.5, 2.0)) | |
| ) | |
| ]), | |
| iaa.LinearContrast((0.5, 2.0), per_channel=0.5), # improve or worsen the contrast | |
| iaa.Grayscale(alpha=(0.0, 1.0)), | |
| sometimes(iaa.ElasticTransformation(alpha=(0.5, 3.5), sigma=0.25)), # move pixels locally around (with random strengths) | |
| sometimes(iaa.PiecewiseAffine(scale=(0.01, 0.05))), # sometimes move parts of the image around | |
| sometimes(iaa.PerspectiveTransform(scale=(0.01, 0.1))) | |
| ], | |
| random_order=True | |
| ) | |
| ], | |
| random_order=True | |
| )) | |