本文整理了Java中org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer类的一些代码示例，展示了Yolo2OutputLayer类的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Yolo2OutputLayer类的具体详情如下：
包路径：org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
类名称：Yolo2OutputLayer

Yolo2OutputLayer介绍

暂无

代码示例

代码示例来源：origin: klevis/AutonomousDriving

public void markWithBoundingBox(Mat file, int imageWidth, int imageHeight, boolean newBoundingBOx,String winName) throws Exception {
  int width = 416;
  int height = 416;
  int gridWidth = 13;
  int gridHeight = 13;
  double detectionThreshold = 0.5;
  Yolo2OutputLayer outputLayer = (Yolo2OutputLayer) preTrained.getOutputLayer(0);
  if (newBoundingBOx) {
    INDArray indArray = prepareImage(file, width, height);
    INDArray results = preTrained.outputSingle(indArray);
    predictedObjects = outputLayer.getPredictedObjects(results, detectionThreshold);
    System.out.println("results = " + predictedObjects);
    markWithBoundingBox(file, gridWidth, gridHeight, imageWidth, imageHeight);
  } else {
    markWithBoundingBox(file, gridWidth, gridHeight, imageWidth, imageHeight);
  }
  imshow(winName, file);
}

代码示例来源：origin: sjsdfg/dl4j-tutorials

INDArray features = ds.getFeatures();
INDArray results = model.outputSingle(features);
List<DetectedObject> objs = yout.getPredictedObjects(results, detectionThreshold);
File file = new File(metadata.getURI());
log.info(file.getName() + ": " + objs);