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 bounding boxes. DetectionOutputParameters defines a set of parameters for creating the DetectionOutput plugin layer. It contains:
More...
#include <NvInferPluginUtils.h>
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 bounding 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. |
isBatchAgnostic | Defaults to true. Set to false if prior boxes are unique per batch |
◆ backgroundLabelId
int32_t nvinfer1::plugin::DetectionOutputParameters::backgroundLabelId |
◆ codeType
CodeTypeSSD nvinfer1::plugin::DetectionOutputParameters::codeType |
◆ confidenceThreshold
float nvinfer1::plugin::DetectionOutputParameters::confidenceThreshold |
◆ confSigmoid
bool nvinfer1::plugin::DetectionOutputParameters::confSigmoid |
◆ inputOrder
int32_t nvinfer1::plugin::DetectionOutputParameters::inputOrder[3] |
◆ isBatchAgnostic
bool nvinfer1::plugin::DetectionOutputParameters::isBatchAgnostic {true} |
◆ isNormalized
bool nvinfer1::plugin::DetectionOutputParameters::isNormalized |
◆ keepTopK
int32_t nvinfer1::plugin::DetectionOutputParameters::keepTopK |
◆ nmsThreshold
float nvinfer1::plugin::DetectionOutputParameters::nmsThreshold |
◆ numClasses
int32_t nvinfer1::plugin::DetectionOutputParameters::numClasses |
◆ shareLocation
bool nvinfer1::plugin::DetectionOutputParameters::shareLocation |
◆ topK
int32_t nvinfer1::plugin::DetectionOutputParameters::topK |
◆ varianceEncodedInTarget
bool nvinfer1::plugin::DetectionOutputParameters::varianceEncodedInTarget |
The documentation for this struct was generated from the following file: