postprocess

package
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 Go to latest Published: Nov 1, 2024 License: Apache-2.0 Imports: 12 Imported by: 0

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Index

Constants

View Source 
const (
	// MaxContours is the maximum number of contours to process on an image
	MaxContours = 1000
	// ContourMinSize is the minimum number size contour
	ContourMinSize = 3
)

Variables

This section is empty.

Functions

func DetectionsToObjects 

func DetectionsToObjects(dets []DetectResult) []tracker.Object

DetectionsToObjects takes a postprocess object detection results and converts it into a tracker object

func NewIDGenerator 

func NewIDGenerator() *idGenerator

Types

type BoxRect 

type BoxRect struct {
	Left   int // Left boundary of the bounding box
	Right  int // Right boundary of the bounding box
	Top    int // Top boundary of the bounding box
	Bottom int // Bottom boundary of the bounding box

	X      int     // X coordinate of the bounding box center
	Y      int     // Y coordinate of the bounding box center
	Width  int     // Width of the bounding box
	Height int     // Height of the bounding box
	Angle  float32 // Rotation angle of the bounding box in radians

	Mode BoxRectMode // Mode indicates how the BoxRect was set
}

BoxRect are the dimensions of the bounding box of a detect object

type BoxRectMode 

type BoxRectMode int

BoxRectMode indicates how the BoxRect was set 

const (
	ModeLTRB BoxRectMode = 0 // (Default) Left, Top, Right, Bottom mode
	ModeXYWH BoxRectMode = 1 // X, Y, Width, Height, Angle mode
)

type DetectResult 

type DetectResult struct {
	// Class is the line number in the labels file the Model was trained on
	// defining the Class of the detected object
	Class int
	// Box are the bounding box dimensions of the object location
	Box BoxRect
	// Probability is the confidence score of the object detected
	Probability float32
	// ID is a unique ID assigned to the detection result
	ID int64
}

DetectResult defines the attributes of a single object detected

type DetectionResult 

type DetectionResult interface {
	GetDetectResults() []DetectResult
}

type KeyPoint 

type KeyPoint struct {
	X     int
	Y     int
	Score float32
}

Keypoint is used for specifying the X, Y coordinates and confidence score of an individual point used in Pose Estimatation

type LPRNet 

type LPRNet struct {
	Params LPRNetParams
}

LPRNet defines the struct for LPRNet model inference post processing

func NewLPRNet 

func NewLPRNet(p LPRNetParams) *LPRNet

NewLPRNet return an instance of the LPRNet post processor

func (*LPRNet) ReadPlates 

func (l *LPRNet) ReadPlates(outputs *rknnlite.Outputs) []string

ReadPlates takes the RKNN outputs and reads out the license plate numbers

type LPRNetParams 

type LPRNetParams struct {
	// PlatePositions is the number of license plate positions to traverse
	PlatePositions int
	// PlateChars are the characters on the number plate used to train the model
	PlateChars []string
	// contains filtered or unexported fields
}

LPRNetParams defines the struct containing the LPRNet parameters to use for post processing operations

type PPOCRBox 

type PPOCRBox struct {
	LeftTop     PPOCRPoint
	RightTop    PPOCRPoint
	RightBottom PPOCRPoint
	LeftBottom  PPOCRPoint
	Score       float32
}

PPOCRBox represents a bounding box with corners and a score

type PPOCRDetect 

type PPOCRDetect struct {
	Params PPOCRDetectParams
}

PPOCRDetect defines the struct for the PPOCR Detection model inference post processing

func NewPPOCRDetect 

func NewPPOCRDetect(param PPOCRDetectParams) *PPOCRDetect

NewPPOCRDetect returns and instance of the PPOCRDetect post processor

func (*PPOCRDetect) Detect 

func (p *PPOCRDetect) Detect(outputs *rknnlite.Outputs, scaleW float32,
	scaleH float32) []PPOCRDetectResult

Detect takes the RKNN oiutputs and converts them to co-ordinates for the bounding boxes of each area of text detected.

func (*PPOCRDetect) GetContourArea 

func (p *PPOCRDetect) GetContourArea(box [][]float32, unclipRatio float32) float32

GetContourArea calculates the area of the contour and returns the distance based on the unclip ratio

type PPOCRDetectParams 

type PPOCRDetectParams struct {
	Threshold    float32
	BoxThreshold float32
	Dilation     bool
	BoxType      string // poly|quad
	UnclipRatio  float32
	ScoreMode    string // slow|fast
	ModelWidth   int
	ModelHeight  int
}

PPOCRDetectParams defines the struct containing the PPOCRDetect parameters to use for post preocessing operations

type PPOCRDetectResult 

type PPOCRDetectResult struct {
	Box []PPOCRBox
}

PPOCRDetectResult is the bounding box result for an area of text detected

type PPOCRPoint 

type PPOCRPoint struct {
	X, Y int
}

PPOCRPoint represents a point with x and y coordinates

type PPOCRRecognise 

type PPOCRRecognise struct {
	Params PPOCRRecogniseParams
}

PPOCRRecognise defines the struct for the PPOCR model inference post processing

func NewPPOCRRecognise 

func NewPPOCRRecognise(param PPOCRRecogniseParams) *PPOCRRecognise

NewPPOCRRecognise returns an instance of the PPOCR post processor

func (*PPOCRRecognise) Recognise 

func (p *PPOCRRecognise) Recognise(outputs *rknnlite.Outputs) []PPOCRRecogniseResult

Recognise takes the RKNN outputs and converts them to text

type PPOCRRecogniseParams 

type PPOCRRecogniseParams struct {
	// ModelChars is the list of characters used to train the PPOCR model
	ModelChars []string

	// OutputSeqLen is the length of sequence output data from the OCR model
	OutputSeqLen int
	// contains filtered or unexported fields
}

PPOCRParams defines the struct containing the PPOCR parameters to use for post processing operations

type PPOCRRecogniseResult 

type PPOCRRecogniseResult struct {
	// Text is the recognised text
	Text string
	// Score is the confidence score of the text recognised
	Score float32
}

PPOCRRecogniseResult is a text result recognised by OCR

type RetinaFace 

type RetinaFace struct {
	// Params are the Model configuration parameters
	Params RetinaFaceParams
	// contains filtered or unexported fields
}

RetinaFace defines the struct for the RetinaFace model inference post processing

func NewRetinaFace 

func NewRetinaFace(p RetinaFaceParams) *RetinaFace

NewRetinaFace returns an instance of the RetinaFace post processor

func (*RetinaFace) DetectFaces 

func (r *RetinaFace) DetectFaces(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectFaces takes the RKNN outputs and runs the face detection process then returns the result

func (*RetinaFace) GetFaceLandmarks 

func (r *RetinaFace) GetFaceLandmarks(detectObjs DetectionResult) [][]KeyPoint

GetFaceLandmarks returns the landmark keypoints for the detected faces

type RetinaFaceParams 

type RetinaFaceParams struct {
	// ConfThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	ConfThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// VisThreshold is the Visualisation threshold
	VisThreshold float32
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
	// KeyPointsNumber is the number of face landmark keypoints representing
	// different features of the face
	KeyPointsNumber int
}

RetinaFaceParams defines the struct containing the RetinaFace parameters to use for post processing operations

func WiderFaceParams 

func WiderFaceParams() RetinaFaceParams

WiderFaceParams returns an instance of RetinaFaceParams configured with the default values for a Model trained on the WIDERFACE dataset featuring: - NMS Threshold: 0.4 - ConfThreshold: 0.5 - VisThreshold: 0.4 - MaxObjectNumber: 128 - KeyPointsNumber: 5

type RetinaFaceResult 

type RetinaFaceResult struct {
	DetectResults []DetectResult
	KeyPoints     [][]KeyPoint
}

RetinaFaceResult defines a struct used for retina face detection results

func (RetinaFaceResult) GetDetectResults 

func (r RetinaFaceResult) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

func (RetinaFaceResult) GetKeyPoints 

func (r RetinaFaceResult) GetKeyPoints() [][]KeyPoint

GetKeyPoints returns the keypoints of the detected faces landmark features

type SegMask 

type SegMask struct {
	// Mask is the segment mask data
	Mask []uint8
}

SegMask defines the segment mask data that is returned with detection results

type SegmentData 

type SegmentData struct {
	// contains filtered or unexported fields
}

SegmentData defines a struct for storing segment data that was created during the object detection phase so we can process segment masks afterwards

type YOLOStride 

type YOLOStride struct {
	// Size is the number of pixels to use for input in each grid section of
	// the image
	Size int
	// Anchor are the Anchor Box presents for the YOLO model used in bounding
	// box predicition for objects
	Anchor []int
}

type YOLOX 

type YOLOX struct {
	// Params are the Model configuration parameters
	Params YOLOXParams
	// contains filtered or unexported fields
}

YOLOX defines the struct for YOLOX model inference post processing

func NewYOLOX 

func NewYOLOX(p YOLOXParams) *YOLOX

NewYOLOX returns an instance of the YOLOX post processor

func (*YOLOX) DetectObjects 

func (y *YOLOX) DetectObjects(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectObjects takes the RKNN outputs and runs the object detection process then returns the results

type YOLOXParams 

type YOLOXParams struct {
	// Strides
	Strides []YOLOStride
	// BoxThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	BoxThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// ObjectClassNum is the number of different object classes the Model has
	// been trained with
	ObjectClassNum int
	// ProbBoxSize is the length of array elements representing each bounding
	// box's attributes.  Which represents the bounding box attributes plus
	// number of objects (ObjectClassNum) the Model was trained with
	ProbBoxSize int
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
}

YOLOXParams defines the struct containing the YOLOX parameters to use for post processing operations

func YOLOXCOCOParams 

func YOLOXCOCOParams() YOLOXParams

YOLOXCOCOParams returns and instance of YOLOXParams configured with default values for a Model trained on the COCO dataset featuring: - Object Classes: 80 - Strides of: 8, 16, 32 - Box Threshold: 0.25 - NMS Threshold: 0.45 - Prob Box Size: 85

  • This is 80 Object Classes plus the 5 attributes used to define a bounding box being:
  • x & y coordinates for the center of the bounding box
  • width and height of the box relative to whole image
  • confidence score

- Maximum Object Number: 64

type YOLOXResult 

type YOLOXResult struct {
	DetectResults []DetectResult
}

YOLOXResult defines a struct used for object detection results

func (YOLOXResult) GetDetectResults 

func (r YOLOXResult) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

type YOLOv10 

type YOLOv10 struct {
	// Params are the Model configuration parameters
	Params YOLOv10Params
	// contains filtered or unexported fields
}

YOLOv10 defines the struct for YOLOv10 model inference post processing

func NewYOLOv10 

func NewYOLOv10(p YOLOv10Params) *YOLOv10

NewYOLOv10 returns an instance of the YOLOv10 post processor

func (*YOLOv10) DetectObjects 

func (y *YOLOv10) DetectObjects(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectObjects takes the RKNN outputs and runs the object detection process then returns the results

type YOLOv10Params 

type YOLOv10Params struct {
	// BoxThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	BoxThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// ObjectClassNum is the number of different object classes the Model has
	// been trained with
	ObjectClassNum int
	// ProbBoxSize is the length of array elements representing each bounding
	// box's attributes.  Which represents the bounding box attributes plus
	// number of objects (ObjectClassNum) the Model was trained with
	ProbBoxSize int
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
}

YOLOv10Params defines the struct containing the YOLOv10 parameters to use for post processing operations

func YOLOv10COCOParams 

func YOLOv10COCOParams() YOLOv10Params

YOLOv10DefaultParams returns an instance of YOLOv10Params configured with default values for a Model trained on the COCO dataset featuring: - Object Classes: 80 - Box Threshold: 0.25 - NMS Threshold: 0.45 - Maximum Object Number: 64

type YOLOv10Result 

type YOLOv10Result struct {
	DetectResults []DetectResult
}

YOLOv10Result defines a struct used for object detection results

func (YOLOv10Result) GetDetectResults 

func (r YOLOv10Result) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

type YOLOv5 

type YOLOv5 struct {
	// Params are the Model configuration parameters
	Params YOLOv5Params
	// contains filtered or unexported fields
}

YOLOv5 defines the struct for YOLOv5 model inference post processing

func NewYOLOv5 

func NewYOLOv5(p YOLOv5Params) *YOLOv5

NewYOLOv5 returns an instance of the YOLOv5 post processor

func (*YOLOv5) DetectObjects 

func (y *YOLOv5) DetectObjects(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectObjects takes the RKNN outputs and runs the object detection process then returns the results

type YOLOv5Params 

type YOLOv5Params struct {
	// Strides
	Strides []YOLOStride
	// BoxThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	BoxThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// ObjectClassNum is the number of different object classes the Model has
	// been trained with
	ObjectClassNum int
	// ProbBoxSize is the length of array elements representing each bounding
	// box's attributes.  Which represents the bounding box attributes plus
	// number of objects (ObjectClassNum) the Model was trained with
	ProbBoxSize int
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
}

YOLOv5Params defines the struct containing the YOLOv5 parameters to use for post processing operations

func YOLOv5COCOParams 

func YOLOv5COCOParams() YOLOv5Params

YOLOv5DefaultParams returns an instance of YOLOv5Params configured with default values for a Model trained on the COCO dataset featuring: - Object Classes: 80 - Anchor Boxes for each Stride of:

  • Stride 8: (10x13), (16x30), (33x23)
  • Stride 16: (30x61), (62x45), (59x119)
  • Stride 32: (116x90), (156x198), (373x326)

- Box Threshold: 0.25 - NMS Threshold: 0.45 - Prob Box Size: 85

  • This is 80 Object Classes plus the 5 attributes used to define a bounding box being:
  • x & y coordinates for the center of the bounding box
  • width and height of the box relative to whole image
  • confidence score

- Maximum Object Number: 64

type YOLOv5Result 

type YOLOv5Result struct {
	DetectResults []DetectResult
}

YOLOv5Result defines a struct used for object detection results

func (YOLOv5Result) GetDetectResults 

func (r YOLOv5Result) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

type YOLOv5Seg 

type YOLOv5Seg struct {
	// Params are the Model configuration parameters
	Params YOLOv5SegParams
	// contains filtered or unexported fields
}

YOLOv5Seg defines the struct for YOLOv5Seg model inference post processing

func NewYOLOv5Seg 

func NewYOLOv5Seg(p YOLOv5SegParams) *YOLOv5Seg

NewYOLOv5Seg returns an instance of the YOLOv5Seg post processor

func (*YOLOv5Seg) DetectObjects 

func (y *YOLOv5Seg) DetectObjects(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectObjects takes the RKNN outputs and runs the object detection process then returns the results

func (*YOLOv5Seg) SegmentMask 

func (y *YOLOv5Seg) SegmentMask(detectObjs DetectionResult,
	resizer *preprocess.Resizer) SegMask

SegmentMask creates segment mask data for object detection results

func (*YOLOv5Seg) TrackMask 

func (y *YOLOv5Seg) TrackMask(detectObjs DetectionResult,
	trackObjs []*tracker.STrack, resizer *preprocess.Resizer) SegMask

TrackMask creates segment mask data for tracked objects

type YOLOv5SegParams 

type YOLOv5SegParams struct {
	// Strides
	Strides []YOLOStride
	// BoxThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	BoxThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// ObjectClassNum is the number of different object classes the Model has
	// been trained with
	ObjectClassNum int
	// ProbBoxSize is the length of array elements representing each bounding
	// box's attributes.  Which represents the bounding box attributes plus
	// number of objects (ObjectClassNum) the Model was trained with
	ProbBoxSize int
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
}

YOLOv5SegParams defines the struct containing the YOLOv5Seg parameters to use for post processing operations

func YOLOv5SegCOCOParams 

func YOLOv5SegCOCOParams() YOLOv5SegParams

YOLOv5SegDefaultParams returns an instance of YOLOv5SegParams configured with default values for a Model trained on the COCO dataset featuring: - Object Classes: 80 - Anchor Boxes for each Stride of:

  • Stride 8: (10x13), (16x30), (33x23)
  • Stride 16: (30x61), (62x45), (59x119)
  • Stride 32: (116x90), (156x198), (373x326)

- Box Threshold: 0.25 - NMS Threshold: 0.45 - Prob Box Size: 85

  • This is 80 Object Classes plus the 5 attributes used to define a bounding box being:
  • x & y coordinates for the center of the bounding box
  • width and height of the box relative to whole image
  • confidence score

- Maximum Object Number: 64

type YOLOv5SegResult 

type YOLOv5SegResult struct {
	DetectResults []DetectResult
	SegmentData   SegmentData
}

YOLOv5SegResult defines a struct used for the results of YOLO segmentation models

func (YOLOv5SegResult) GetDetectResults 

func (r YOLOv5SegResult) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

func (YOLOv5SegResult) GetSegmentData 

func (r YOLOv5SegResult) GetSegmentData() SegmentData

type YOLOv8 

type YOLOv8 struct {
	// Params are the Model configuration parameters
	Params YOLOv8Params
	// contains filtered or unexported fields
}

YOLOv8 defines the struct for YOLOv8 model inference post processing

func NewYOLOv8 

func NewYOLOv8(p YOLOv8Params) *YOLOv8

NewYOLOv8 returns an instance of the YOLOv8 post processor

func (*YOLOv8) DetectObjects 

func (y *YOLOv8) DetectObjects(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectObjects takes the RKNN outputs and runs the object detection process then returns the results

type YOLOv8Params 

type YOLOv8Params struct {
	// BoxThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	BoxThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// ObjectClassNum is the number of different object classes the Model has
	// been trained with
	ObjectClassNum int
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
}

YOLOv8Params defines the struct containing the YOLOv8 parameters to use for post processing operations

func YOLOv8COCOParams 

func YOLOv8COCOParams() YOLOv8Params

YOLOv8DefaultParams returns an instance of YOLOv8Params configured with default values for a Model trained on the COCO dataset featuring: - Object Classes: 80 - Box Threshold: 0.25 - NMS Threshold: 0.45 - Maximum Object Number: 64

type YOLOv8Pose 

type YOLOv8Pose struct {
	// Params are the Model configuration parameters
	Params YOLOv8PoseParams
	// contains filtered or unexported fields
}

YOLOv8Pose defines the struct for YOLOv8 model inference post processing

func NewYOLOv8Pose 

func NewYOLOv8Pose(p YOLOv8PoseParams) *YOLOv8Pose

NewYOLOv8Pose returns an instance of the YOLOv8Pose post processor

func (*YOLOv8Pose) DetectObjects 

func (y *YOLOv8Pose) DetectObjects(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectObjects takes the RKNN outputs and runs the object detection process then returns the results

func (*YOLOv8Pose) GetPoseEstimation 

func (y *YOLOv8Pose) GetPoseEstimation(detectObjs DetectionResult) [][]KeyPoint

GetPoseEstimation returns the keypoints for the detection objects used in pose estimation

type YOLOv8PoseParams 

type YOLOv8PoseParams struct {
	// BoxThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	BoxThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// ObjectClassNum is the number of different object classes the Model has
	// been trained with
	ObjectClassNum int
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
	// KeyPointsNumber is the number of COCO keypoints representing different parts
	// of the body the pose model is trained on
	KeyPointsNumber int
}

YOLOv8PoseParams defines the struct containing the YOLOv8 parameters to use for post processing operations

func YOLOv8PoseCOCOParams 

func YOLOv8PoseCOCOParams() YOLOv8PoseParams

YOLOv8PoseDefaultParams returns an instance of YOLOv8PoseParams configured with default values for a Model trained on the COCO dataset featuring: - Object Classes: 1 - Box Threshold: 0.5 - NMS Threshold: 0.4 - Maximum Object Number: 64 - KeyPoints Number: 17

type YOLOv8PoseResult 

type YOLOv8PoseResult struct {
	DetectResults []DetectResult
	KeyPoints     [][]KeyPoint
}

YOLOv8PoseResult defines a struct used for object detection results

func (YOLOv8PoseResult) GetDetectResults 

func (r YOLOv8PoseResult) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

func (YOLOv8PoseResult) GetKeyPoints 

func (r YOLOv8PoseResult) GetKeyPoints() [][]KeyPoint

type YOLOv8Result 

type YOLOv8Result struct {
	DetectResults []DetectResult
}

YOLOv8Result defines a struct used for object detection results

func (YOLOv8Result) GetDetectResults 

func (r YOLOv8Result) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

type YOLOv8Seg 

type YOLOv8Seg struct {
	// Params are the Model configuration parameters
	Params YOLOv8SegParams
	// contains filtered or unexported fields
}

YOLOv8Seg defines the struct for YOLOv8Seg model inference post processing

func NewYOLOv8Seg 

func NewYOLOv8Seg(p YOLOv8SegParams) *YOLOv8Seg

NewYOLOv8 returns an instance of the YOLOv8Seg post processor

func (*YOLOv8Seg) DetectObjects 

func (y *YOLOv8Seg) DetectObjects(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectObjects takes the RKNN outputs and runs the object detection process then returns the results

func (*YOLOv8Seg) SegmentMask 

func (y *YOLOv8Seg) SegmentMask(detectObjs DetectionResult,
	resizer *preprocess.Resizer) SegMask

SegmentMask creates segment mask data for object detection results

func (*YOLOv8Seg) TrackMask 

func (y *YOLOv8Seg) TrackMask(detectObjs DetectionResult,
	trackObjs []*tracker.STrack, resizer *preprocess.Resizer) SegMask

TrackMask creates segment mask data for tracked objects

type YOLOv8SegParams 

type YOLOv8SegParams struct {
	// BoxThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	BoxThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// ObjectClassNum is the number of different object classes the Model has
	// been trained with
	ObjectClassNum int
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
}

YOLOv8SegParams defines the struct containing the YOLOv8Seg parameters to use for post processing operations

func YOLOv8SegCOCOParams 

func YOLOv8SegCOCOParams() YOLOv8SegParams

YOLOv8SegDefaultParams returns an instance of YOLOv8SegParams configured with default values for a Model trained on the COCO dataset featuring: - Object Classes: 80 - Box Threshold: 0.25 - NMS Threshold: 0.45 - Maximum Object Number: 64

type YOLOv8SegResult 

type YOLOv8SegResult struct {
	DetectResults []DetectResult
	SegmentData   SegmentData
}

YOLOv8SegResult defines a struct used for object detection results

func (YOLOv8SegResult) GetDetectResults 

func (r YOLOv8SegResult) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

func (YOLOv8SegResult) GetSegmentData 

func (r YOLOv8SegResult) GetSegmentData() SegmentData

type YOLOv8obb 

type YOLOv8obb struct {
	// Params are the Model configuration parameters
	Params YOLOv8obbParams
	// contains filtered or unexported fields
}

YOLOv8obb defines the struct for YOLOv8-obb model inference post processing

func NewYOLOv8obb 

func NewYOLOv8obb(p YOLOv8obbParams) *YOLOv8obb

NewYOLOv8obb returns an instance of the YOLOv8obb post processor

func (*YOLOv8obb) DetectObjects 

func (y *YOLOv8obb) DetectObjects(outputs *rknnlite.Outputs,
	resizer *preprocess.Resizer) DetectionResult

DetectObjects takes the RKNN outputs and runs the object detection process then returns the results

type YOLOv8obbParams 

type YOLOv8obbParams struct {
	// BoxThreshold is the minimum probability score required for a bounding box
	// region to be considered for processing
	BoxThreshold float32
	// NMSThreshold is the Non-Maximum Suppression threshold used for defining
	// the maximum allowed Intersection Over Union (IoU) between two
	// bounding boxes for both to be kept
	NMSThreshold float32
	// ObjectClassNum is the number of different object classes the Model has
	// been trained with
	ObjectClassNum int
	// MaxObjectNumber is the maximum number of objects detected that can be
	// returned
	MaxObjectNumber int
}

YOLOv8obbParams defines the struct containing the YOLOv8-obb parameters to use for post processing operations

func YOLOv8obbDOTAv1Params 

func YOLOv8obbDOTAv1Params() YOLOv8obbParams

YOLOv8obbDOTAv1Params returns an instance of YOLOv8obbParams configured with default values for a Model trained on the DOTAv1 dataset - Object Classes: 15 - Box Threshold: 0.5 - NMS Threshold: 0.4 - Maximum Object Number: 64

type YOLOv8obbResult 

type YOLOv8obbResult struct {
	DetectResults []DetectResult
}

YOLOv8obbResult defines a struct used for object detection results

func (YOLOv8obbResult) GetDetectResults 

func (r YOLOv8obbResult) GetDetectResults() []DetectResult

GetDetectResults returns the object detection results containing bounding boxes

Source Files

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