aleju--imgaug
wehub-resource-sync
71 行
2.5 KiB
Python
71 行
2.5 KiB
Python
from __future__ import print_function, division
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import numpy as np
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import imgaug as ia
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from imgaug import augmenters as iaa
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from imgaug import parameters as iap
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def main():
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nb_rows = 8
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nb_cols = 8
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h, w = (128, 128)
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sample_size = 128
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noise_gens = [
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iap.SimplexNoise(),
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iap.FrequencyNoise(exponent=-4, size_px_max=sample_size, upscale_method="cubic"),
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iap.FrequencyNoise(exponent=-2, size_px_max=sample_size, upscale_method="cubic"),
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iap.FrequencyNoise(exponent=0, size_px_max=sample_size, upscale_method="cubic"),
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iap.FrequencyNoise(exponent=2, size_px_max=sample_size, upscale_method="cubic"),
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iap.FrequencyNoise(exponent=4, size_px_max=sample_size, upscale_method="cubic"),
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iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size),
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upscale_method=["nearest", "linear", "cubic"]),
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iap.IterativeNoiseAggregator(
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other_param=iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size),
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upscale_method=["nearest", "linear", "cubic"]),
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iterations=(1, 3),
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aggregation_method=["max", "avg"]
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),
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iap.IterativeNoiseAggregator(
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other_param=iap.Sigmoid(
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iap.FrequencyNoise(exponent=(-4, 4), size_px_max=(4, sample_size),
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upscale_method=["nearest", "linear", "cubic"]),
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threshold=(-10, 10),
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activated=0.33,
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mul=20,
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add=-10
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),
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iterations=(1, 3),
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aggregation_method=["max", "avg"]
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)
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]
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samples = [[] for _ in range(len(noise_gens))]
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for _ in range(nb_rows * nb_cols):
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for i, noise_gen in enumerate(noise_gens):
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samples[i].append(noise_gen.draw_samples((h, w)))
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rows = [np.hstack(row) for row in samples]
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grid = np.vstack(rows)
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ia.imshow((grid*255).astype(np.uint8))
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images = [ia.quokka_square(size=(128, 128)) for _ in range(16)]
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seqs = [
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iaa.SimplexNoiseAlpha(first=iaa.EdgeDetect(1.0)),
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iaa.SimplexNoiseAlpha(first=iaa.EdgeDetect(1.0), per_channel=True),
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iaa.FrequencyNoiseAlpha(first=iaa.EdgeDetect(1.0)),
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iaa.FrequencyNoiseAlpha(first=iaa.EdgeDetect(1.0), per_channel=True)
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]
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images_aug = []
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for seq in seqs:
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images_aug.append(np.hstack(seq.augment_images(images)))
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images_aug = np.vstack(images_aug)
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ia.imshow(images_aug)
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if __name__ == "__main__":
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main()
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