org.apache.mxnet.infer.javaapi

ObjectDetector

Related Docs: object ObjectDetector | package javaapi

class ObjectDetector extends AnyRef

The ObjectDetector class helps to run ObjectDetection tasks where the goal is to find bounding boxes and corresponding labels for objects in a image.

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Instance Constructors

  1. new ObjectDetector(modelPathPrefix: String, inputDescriptors: List[javaapi.DataDesc], contexts: List[javaapi.Context], epoch: Int)

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  12. def imageBatchObjectDetect(inputBatch: List[BufferedImage], topK: Int): List[List[ObjectDetectorOutput]]

    To classify batch of input images according to the provided model

    To classify batch of input images according to the provided model

    inputBatch

    Input array of buffered images

    topK

    Number of result elements to return, sorted by probability

    returns

    List of list of tuples of (class, probability)

  13. def imageObjectDetect(inputImage: BufferedImage, topK: Int): List[List[ObjectDetectorOutput]]

    Detects objects and returns bounding boxes with corresponding class/label

    Detects objects and returns bounding boxes with corresponding class/label

    inputImage

    Path prefix of the input image

    topK

    Number of result elements to return, sorted by probability

    returns

    List of list of tuples of (class, [probability, xmin, ymin, xmax, ymax])

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  16. final def notify(): Unit

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  18. val objDetector: infer.ObjectDetector

  19. def objectDetectWithNDArray(input: List[javaapi.NDArray], topK: Int): List[List[ObjectDetectorOutput]]

    Takes input images as NDArrays.

    Takes input images as NDArrays. Useful when you want to perform multiple operations on the input array, or when you want to pass a batch of input images.

    input

    Indexed Sequence of NDArrays

    topK

    (Optional) How many top_k (sorting will be based on the last axis) elements to return. If not passed, returns all unsorted output.

    returns

    List of list of tuples of (class, [probability, xmin, ymin, xmax, ymax])

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