Image

Built-in pipelines for preprocessing, agumentating and predicting.

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AugmentImage

paz.pipelines.image.AugmentImage()

Augments an RGB image by randomly changing contrast, brightness saturation and hue.

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PreprocessImage

paz.pipelines.image.PreprocessImage(shape, mean=(104, 117, 123))

Preprocess RGB image by resizing it to the given shape. If a mean is given it is substracted from image and it not the image gets normalized.

Arguments

• shape: List of two Ints.
• mean: List of three Ints indicating the per-channel mean to be subtracted.

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DecoderPredictor

paz.pipelines.image.DecoderPredictor(decoder)

Pipeline for predicting decoded image from a latent vector.

Arguments

• model: Keras model.

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EncoderPredictor

paz.pipelines.image.EncoderPredictor(encoder)

Pipeline for predicting latent vector of an encoder.

Arguments

• model: Keras model.

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PreprocessImageHigherHRNet

paz.pipelines.image.PreprocessImageHigherHRNet(scaling_factor=200, input_size=512, multiple=64)

Transform the image according to the HigherHRNet model requirement. Arguments

• scaling_factor: Int. scale factor for image dimensions.
• input_size: Int. resize the first dimension of image to input size.
• inverse: Boolean. Reverse the affine transform input.
• image: Numpy array. Input image

Returns

• image: resized and transformed image
• center: center of the image
• scale: scaled image dimensions