nvinfer1::plugin Namespace Reference

Classes
struct	DetectionOutputParameters
	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...
struct	GridAnchorParameters
	The Anchor Generator plugin layer generates the prior boxes of designated sizes and aspect ratios across all dimensions (H x W). GridAnchorParameters defines a set of parameters for creating the plugin layer for all feature maps. It contains: More...
struct	NMSParameters
	The NMSParameters are used by the BatchedNMSPlugin for performing the non_max_suppression operation over boxes for object detection networks. More...
struct	PriorBoxParameters
	The PriorBox plugin layer generates the prior boxes of designated sizes and aspect ratios across all dimensions (H x W). PriorBoxParameters defines a set of parameters for creating the PriorBox plugin layer. It contains: More...
struct	Quadruple
	The Permute plugin layer permutes the input tensor by changing the memory order of the data. Quadruple defines a structure that contains an array of 4 integers. They can represent the permute orders or the strides in each dimension. More...
struct	RegionParameters
	The Region plugin layer performs region proposal calculation: generate 5 bounding boxes per cell (for yolo9000, generate 3 bounding boxes per cell). For each box, calculating its probablities of objects detections from 80 pre-defined classifications (yolo9000 has 9418 pre-defined classifications, and these 9418 items are organized as work-tree structure). RegionParameters defines a set of parameters for creating the Region plugin layer. More...
struct	RPROIParams
	RPROIParams is used to create the RPROIPlugin instance. It contains: More...
struct	softmaxTree
	When performing yolo9000, softmaxTree is helping to do softmax on confidence scores, for element to get the precise classification through word-tree structured classification definition. More...

Enumerations
enum class	CodeTypeSSD : int32_t { CORNER = 0 , CENTER_SIZE = 1 , CORNER_SIZE = 2 , TF_CENTER = 3 }
	The type of encoding used for decoding the bounding boxes and loc_data. More...

Enumeration Type Documentation

CodeTypeSSD

enum class nvinfer1::plugin::CodeTypeSSD : int32_t

strong

The type of encoding used for decoding the bounding boxes and loc_data.

Enumerator
CORNER	Use box corners.
CENTER_SIZE	Use box centers and size.
CORNER_SIZE	Use box centers and size.
TF_CENTER	Use box centers and size but flip x and y coordinates.