Package ai.djl.training.loss

Class YOLOv3Loss

java.lang.Object
ai.djl.training.evaluator.Evaluator
ai.djl.training.loss.Loss
ai.djl.training.loss.YOLOv3Loss
public final class YOLOv3Loss extends Loss
YOLOv3Loss is an implementation of Loss. It is used to compute the loss while training a YOLOv3 model for object detection. It involves computing the targets given the generated anchors, labels and predictions, and then computing the sum of class predictions and bounding box predictions.

  • Method Details

    • getPresetAnchors

      public static float[] getPresetAnchors()
      Gets the preset anchors of YoloV3.
      Returns:
      the preset anchors of YoloV3

    • clipByTensor

      public NDArray clipByTensor(NDArray tList, float tMin, float tMax)
      Make the value of given NDArray between tMin and tMax.
      Parameters:
      tList - the given NDArray
      tMin - the min value
      tMax - the max value
      Returns:
      a NDArray where values are set between tMin and tMax

    • mseLoss

      public NDArray mseLoss(NDArray prediction, NDArray target)
      Calculates the MSELoss between prediction and target.
      Parameters:
      prediction - the prediction array
      target - the target array
      Returns:
      the MSELoss between prediction and target

    • bceLoss

      public NDArray bceLoss(NDArray prediction, NDArray target)
      Calculates the BCELoss between prediction and target.
      Parameters:
      prediction - the prediction array
      target - the target array
      Returns:
      the BCELoss between prediction and target

    • evaluate

      public NDArray evaluate(NDList labels, NDList predictions)
      Calculates the evaluation between the labels and the predictions.
      Specified by:
      evaluate in class Evaluator
      Parameters:
      labels - the correct values
      predictions - the predicted values
      Returns:
      the evaluation result

    • evaluateOneOutput

      public NDArray evaluateOneOutput(int componentIndex, NDArray input, NDArray labels)
      Computes the Loss for one outputLayer.
      Parameters:
      componentIndex - which outputLayer does current input represent. the shape should be (13*13,26*26,52*52)
      input - one prediction layer of YOLOv3
      labels - target labels. Must contain (offsetLabels, masks, classlabels)
      Returns:
      the total loss of a outputLayer

    • getTarget

      public NDList getTarget(NDArray labels, int inH, int inW)
      Gets target NDArray for a given evaluator.
      Parameters:
      labels - the true labels
      inH - the height of current layer
      inW - the width of current layer
      Returns:
      an NDList of {boxLossScale and groundTruth}

    • calculateIOU

      public NDArray calculateIOU(NDArray predx, NDArray predy, NDArray groundTruth, int componentIndex)
      Calculates the IOU between priori Anchors and groundTruth.
      Parameters:
      predx - the tx value of prediction
      predy - the ty value of prediction
      groundTruth - the groundTruth value of labels
      componentIndex - the current component Index
      Returns:
      an NDArray of IOU

    • builder

      public static YOLOv3Loss.Builder builder()
      Creates a new builder to build a YOLOv3Loss.
      Returns:
      a new builder;