Package | Description |
---|---|
org.deeplearning4j.nn.adapters | |
org.deeplearning4j.nn.layers.objdetect |
Modifier and Type | Method and Description |
---|---|
List<DetectedObject> |
YoloModelAdapter.apply(INDArray... outputs) |
List<DetectedObject> |
YoloModelAdapter.apply(Model model,
INDArray[] inputs,
INDArray[] masks,
INDArray[] labelsMasks) |
Modifier and Type | Method and Description |
---|---|
List<DetectedObject> |
Yolo2OutputLayer.getPredictedObjects(INDArray networkOutput,
double threshold) |
static List<DetectedObject> |
YoloUtils.getPredictedObjects(INDArray boundingBoxPriors,
INDArray networkOutput,
double confThreshold,
double nmsThreshold)
Given the network output and a detection threshold (in range 0 to 1) determine the objects detected by
the network.
Supports minibatches - the returned DetectedObject instances have an example number index.Note that the dimensions are grid cell units - for example, with 416x416 input, 32x downsampling by the network (before getting to the Yolo2OutputLayer) we have 13x13 grid cells (each corresponding to 32 pixels in the input image). |
Modifier and Type | Method and Description |
---|---|
static double |
YoloUtils.iou(DetectedObject o1,
DetectedObject o2)
Returns intersection over union (IOU) between o1 and o2.
|
Modifier and Type | Method and Description |
---|---|
static void |
YoloUtils.nms(List<DetectedObject> objects,
double iouThreshold)
Performs non-maximum suppression (NMS) on objects, using their IOU with threshold to match pairs.
|
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