The DetectionOutput plugin layer generates the detection output based on location and confidence predictions by doing non maximum suppression.
This plugin first decodes the bounding boxes based on the anchors generated. It then performs non_max_suppression on the decoded bouding boxes. DetectionOutputParameters defines a set of parameters for creating the DetectionOutput plugin layer. It contains:
- Parameters
-
shareLocation | If true, bounding box are shared among different classes. |
varianceEncodedInTarget | If true, variance is encoded in target. Otherwise we need to adjust the predicted offset accordingly. |
backgroundLabelId | Background label ID. If there is no background class, set it as -1. |
numClasses | Number of classes to be predicted. |
topK | Number of boxes per image with top confidence scores that are fed into the NMS algorithm. |
keepTopK | Number of total bounding boxes to be kept per image after NMS step. |
confidenceThreshold | Only consider detections whose confidences are larger than a threshold. |
nmsThreshold | Threshold to be used in NMS. |
codeType | Type of coding method for bbox. |
inputOrder | Specifies the order of inputs {loc_data, conf_data, priorbox_data}. |
confSigmoid | Set to true to calculate sigmoid of confidence scores. |
isNormalized | Set to true if bounding box data is normalized by the network. |