object ImageTransformer extends DefaultParamsReadable[ImageTransformer] with Serializable
Pipelined image processing.
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def
convertToTensor(matrices: Array[Mat]): Array[Array[Array[Double]]]
Convert channel matrices to tensor in the shape of (C * H * W)
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def
decodeImage(decodeMode: String)(r: Any): Option[(String, Mat)]
Convert Spark image representation to OpenCV format.
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def
encodeImage(path: String, image: Mat): Row
Convert from OpenCV format to Dataframe Row.
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def
extractChannels(channelOrder: String)(image: Mat): Array[Mat]
Extract channels from image.
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def
load(path: String): ImageTransformer
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- ImageTransformer → MLReadable
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def
normalizeChannels(means: Option[Array[Double]], stds: Option[Array[Double]], scaleFactor: Option[Double])(channels: Array[Mat]): Array[Mat]
Normalize each channel.
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def
processImage(stages: Seq[ImageTransformerStage])(image: Mat): Mat
Apply all OpenCV transformation stages to a single image.
Apply all OpenCV transformation stages to a single image. Break on OpenCV errors.
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read: MLReader[ImageTransformer]
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