class Lighting extends Transformer[LabeledBGRImage, LabeledBGRImage]
Lighting noise for data augmentation
Krizhevsky et al. proposed fancy PCA when training the famous Alex-Net in 2012 Fancy PCA alters the intensities of the RGB channels in training images For each training image, add the corresponding quantity to each RGB image pixel
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##(): Int
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def
->[C](other: Transformer[LabeledBGRImage, C]): Transformer[LabeledBGRImage, C]
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- val alphastd: Float
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def
apply(prev: Iterator[LabeledBGRImage]): Iterator[LabeledBGRImage]
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def
apply(dataset: RDD[LabeledBGRImage])(implicit evidence: ClassTag[LabeledBGRImage]): RDD[LabeledBGRImage]
Apply this transformer to rdd
Apply this transformer to rdd
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cloneTransformer(): Transformer[LabeledBGRImage, LabeledBGRImage]
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- val eigval: Tensor[Float]
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- def lighting(input: Array[Float]): Unit
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