object MAPUtil
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def
gtTablesToGroundTruthRegions(gtTable: Table, classes: Int, numIOU: Int, isCOCO: Boolean, isSegmentation: Boolean): (Array[ArrayBuffer[GroundTruthRegion]], Array[Int])
convert the ground truth into parsed GroundTruthRegions
convert the ground truth into parsed GroundTruthRegions
- isCOCO
if using COCO's algorithm for IOU computation
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(array of GT BBoxes of images, # of GT bboxes for each class)
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def
parseDetection(gtBbox: ArrayBuffer[GroundTruthRegion], label: Int, score: Float, x1: Float, y1: Float, x2: Float, y2: Float, mask: RLEMasks, classes: Int, iou: Array[Float], predictByClasses: Array[Array[ArrayBuffer[(Float, Boolean)]]]): Unit
For a detection, match it with all GT boxes.
For a detection, match it with all GT boxes. Record the match in "predictByClass"
- def parseSegmentationTensorResult(outTensor: Tensor[Float], func: (Int, Int, Float, Float, Float, Float, Float) ⇒ Unit): Unit
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