c

com.intel.analytics.bigdl.optim

MeanAveragePrecisionObjectDetection

class MeanAveragePrecisionObjectDetection[T] extends ValidationMethod[T]

MeanAveragePrecision for Object Detection The class label begins with 0

The expected output from the last layer should be a Tensor[Float] or a Table If output is a tensor, it should be [num_of_batch X (1 + maxDetection * 6)] matrix The format of the matrix should be [<batch>, <batch>, ...], where each row vector is <batch> = [<size_of_batch>, <sample>,...]. Each sample has format: <sample> = <label, score, bbox x4> imgId is the batch number of the sample. imgId begins with 0. Multiple samples may share one imgId

If output is a table, it is a table of tables. output(i) is the results of the i-th image in the batch, where i = 1 to sizeof(batch) output(i) is a table, which contains the same keys (fields) of image info in the "target" Please refer to RoiMiniBatch/RoiImageInfo's documents. Besides, the inner tables also contain the scores for the detections in the image.

The "target" (Ground truth) is a table with the same structure of "output", except that it does not have "score" field

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Instance Constructors

  1. new MeanAveragePrecisionObjectDetection(classes: Int, topK: Int = -1, iouThres: Array[Float] = Array(0.5f), theType: MAPType = MAPPascalVoc2010, skipClass: Int = -1, isSegmentation: Boolean = false)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    classes

    the number of classes

    topK

    only take topK confident predictions (-1 for all predictions)

    iouThres

    the IOU thresholds

    theType

    the type of MAP algorithm. (voc2007/voc2010/COCO)

    skipClass

    skip calculating on a specific class (e.g. background) the class index starts from 0, or is -1 if no skipping

    isSegmentation

    if check the IOU of segmentations instead of bounding boxes. If true, the output and target must have "masks" data

Value Members

  1. final def !=(arg0: Any): Boolean
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  4. def apply(output: Activity, target: Activity): ValidationResult
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    MeanAveragePrecisionObjectDetection → ValidationMethod
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  6. def clone(): ValidationMethod[T]
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  10. def format(): String
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