mirror of
https://github.com/hybridgroup/gocv
synced 2025-08-25 08:41:04 +08:00
286 lines
9.1 KiB
Go
286 lines
9.1 KiB
Go
package gocv
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/*
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#include <stdlib.h>
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#include "objdetect.h"
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*/
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import "C"
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import (
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"image"
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"unsafe"
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)
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// CascadeClassifier is a cascade classifier class for object detection.
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//
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// For further details, please see:
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// http://docs.opencv.org/master/d1/de5/classcv_1_1CascadeClassifier.html
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//
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type CascadeClassifier struct {
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p C.CascadeClassifier
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}
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// NewCascadeClassifier returns a new CascadeClassifier.
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func NewCascadeClassifier() CascadeClassifier {
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return CascadeClassifier{p: C.CascadeClassifier_New()}
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}
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// Close deletes the CascadeClassifier's pointer.
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func (c *CascadeClassifier) Close() error {
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C.CascadeClassifier_Close(c.p)
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c.p = nil
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return nil
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}
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// Load cascade classifier from a file.
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//
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// For further details, please see:
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// http://docs.opencv.org/master/d1/de5/classcv_1_1CascadeClassifier.html#a1a5884c8cc749422f9eb77c2471958bc
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//
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func (c *CascadeClassifier) Load(name string) bool {
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cName := C.CString(name)
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defer C.free(unsafe.Pointer(cName))
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return C.CascadeClassifier_Load(c.p, cName) != 0
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}
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// DetectMultiScale detects objects of different sizes in the input Mat image.
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// The detected objects are returned as a slice of image.Rectangle structs.
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//
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// For further details, please see:
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// http://docs.opencv.org/master/d1/de5/classcv_1_1CascadeClassifier.html#aaf8181cb63968136476ec4204ffca498
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//
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func (c *CascadeClassifier) DetectMultiScale(img Mat) []image.Rectangle {
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ret := C.CascadeClassifier_DetectMultiScale(c.p, img.p)
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defer C.Rects_Close(ret)
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return toRectangles(ret)
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}
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// DetectMultiScaleWithParams calls DetectMultiScale but allows setting parameters
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// to values other than just the defaults.
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//
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// For further details, please see:
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// http://docs.opencv.org/master/d1/de5/classcv_1_1CascadeClassifier.html#aaf8181cb63968136476ec4204ffca498
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//
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func (c *CascadeClassifier) DetectMultiScaleWithParams(img Mat, scale float64,
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minNeighbors, flags int, minSize, maxSize image.Point) []image.Rectangle {
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minSz := C.struct_Size{
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width: C.int(minSize.X),
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height: C.int(minSize.Y),
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}
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maxSz := C.struct_Size{
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width: C.int(maxSize.X),
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height: C.int(maxSize.Y),
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}
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ret := C.CascadeClassifier_DetectMultiScaleWithParams(c.p, img.p, C.double(scale),
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C.int(minNeighbors), C.int(flags), minSz, maxSz)
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defer C.Rects_Close(ret)
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return toRectangles(ret)
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}
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// HOGDescriptor is a Histogram Of Gradiants (HOG) for object detection.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d5/d33/structcv_1_1HOGDescriptor.html#a723b95b709cfd3f95cf9e616de988fc8
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//
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type HOGDescriptor struct {
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p C.HOGDescriptor
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}
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// NewHOGDescriptor returns a new HOGDescriptor.
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func NewHOGDescriptor() HOGDescriptor {
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return HOGDescriptor{p: C.HOGDescriptor_New()}
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}
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// Close deletes the HOGDescriptor's pointer.
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func (h *HOGDescriptor) Close() error {
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C.HOGDescriptor_Close(h.p)
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h.p = nil
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return nil
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}
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// DetectMultiScale detects objects in the input Mat image.
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// The detected objects are returned as a slice of image.Rectangle structs.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d5/d33/structcv_1_1HOGDescriptor.html#a660e5cd036fd5ddf0f5767b352acd948
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//
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func (h *HOGDescriptor) DetectMultiScale(img Mat) []image.Rectangle {
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ret := C.HOGDescriptor_DetectMultiScale(h.p, img.p)
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defer C.Rects_Close(ret)
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return toRectangles(ret)
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}
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// DetectMultiScaleWithParams calls DetectMultiScale but allows setting parameters
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// to values other than just the defaults.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d5/d33/structcv_1_1HOGDescriptor.html#a660e5cd036fd5ddf0f5767b352acd948
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//
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func (h *HOGDescriptor) DetectMultiScaleWithParams(img Mat, hitThresh float64,
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winStride, padding image.Point, scale, finalThreshold float64, useMeanshiftGrouping bool) []image.Rectangle {
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wSz := C.struct_Size{
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width: C.int(winStride.X),
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height: C.int(winStride.Y),
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}
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pSz := C.struct_Size{
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width: C.int(padding.X),
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height: C.int(padding.Y),
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}
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ret := C.HOGDescriptor_DetectMultiScaleWithParams(h.p, img.p, C.double(hitThresh),
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wSz, pSz, C.double(scale), C.double(finalThreshold), C.bool(useMeanshiftGrouping))
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defer C.Rects_Close(ret)
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return toRectangles(ret)
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}
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// HOGDefaultPeopleDetector returns a new Mat with the HOG DefaultPeopleDetector.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d5/d33/structcv_1_1HOGDescriptor.html#a660e5cd036fd5ddf0f5767b352acd948
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//
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func HOGDefaultPeopleDetector() Mat {
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return newMat(C.HOG_GetDefaultPeopleDetector())
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}
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// SetSVMDetector sets the data for the HOGDescriptor.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d5/d33/structcv_1_1HOGDescriptor.html#a09e354ad701f56f9c550dc0385dc36f1
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//
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func (h *HOGDescriptor) SetSVMDetector(det Mat) error {
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C.HOGDescriptor_SetSVMDetector(h.p, det.p)
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return nil
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}
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// GroupRectangles groups the object candidate rectangles.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d5/d54/group__objdetect.html#ga3dba897ade8aa8227edda66508e16ab9
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//
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func GroupRectangles(rects []image.Rectangle, groupThreshold int, eps float64) []image.Rectangle {
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cRectArray := make([]C.struct_Rect, len(rects))
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for i, r := range rects {
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cRect := C.struct_Rect{
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x: C.int(r.Min.X),
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y: C.int(r.Min.Y),
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width: C.int(r.Size().X),
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height: C.int(r.Size().Y),
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}
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cRectArray[i] = cRect
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}
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cRects := C.struct_Rects{
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rects: (*C.Rect)(&cRectArray[0]),
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length: C.int(len(rects)),
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}
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ret := C.GroupRectangles(cRects, C.int(groupThreshold), C.double(eps))
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return toRectangles(ret)
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}
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// QRCodeDetector groups the object candidate rectangles.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/de/dc3/classcv_1_1QRCodeDetector.html
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//
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type QRCodeDetector struct {
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p C.QRCodeDetector
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}
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// newQRCodeDetector returns a new QRCodeDetector from a C QRCodeDetector
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func newQRCodeDetector(p C.QRCodeDetector) QRCodeDetector {
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return QRCodeDetector{p: p}
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}
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func NewQRCodeDetector() QRCodeDetector {
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return newQRCodeDetector(C.QRCodeDetector_New())
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}
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func (a *QRCodeDetector) Close() error {
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C.QRCodeDetector_Close(a.p)
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a.p = nil
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return nil
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}
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// DetectAndDecode Both detects and decodes QR code.
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//
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// Returns true as long as some QR code was detected even in case where the decoding failed
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// For further details, please see:
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// https://docs.opencv.org/master/de/dc3/classcv_1_1QRCodeDetector.html#a7290bd6a5d59b14a37979c3a14fbf394
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//
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func (a *QRCodeDetector) DetectAndDecode(input Mat, points *Mat, straight_qrcode *Mat) string {
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goResult := C.GoString(C.QRCodeDetector_DetectAndDecode(a.p, input.p, points.p, straight_qrcode.p))
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return string(goResult)
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}
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// Detect detects QR code in image and returns the quadrangle containing the code.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/de/dc3/classcv_1_1QRCodeDetector.html#a64373f7d877d27473f64fe04bb57d22b
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//
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func (a *QRCodeDetector) Detect(input Mat, points *Mat) bool {
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result := C.QRCodeDetector_Detect(a.p, input.p, points.p)
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return bool(result)
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}
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// Decode decodes QR code in image once it's found by the detect() method. Returns UTF8-encoded output string or empty string if the code cannot be decoded.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/de/dc3/classcv_1_1QRCodeDetector.html#a4172c2eb4825c844fb1b0ae67202d329
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//
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func (a *QRCodeDetector) Decode(input Mat, points Mat, straight_qrcode *Mat) string {
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goResult := C.GoString(C.QRCodeDetector_DetectAndDecode(a.p, input.p, points.p, straight_qrcode.p))
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return string(goResult)
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}
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// Detects QR codes in image and finds of the quadrangles containing the codes.
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//
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// Each quadrangle would be returned as a row in the `points` Mat and each point is a Vecf.
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// Returns true if QR code was detected
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// For usage please see TestQRCodeDetector
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// For further details, please see:
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// https://docs.opencv.org/master/de/dc3/classcv_1_1QRCodeDetector.html#aaf2b6b2115b8e8fbc9acf3a8f68872b6
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func (a *QRCodeDetector) DetectMulti(input Mat, points *Mat) bool {
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result := C.QRCodeDetector_DetectMulti(a.p, input.p, points.p)
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return bool(result)
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}
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// Detects QR codes in image, finds the quadrangles containing the codes, and decodes the QRCodes to strings.
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//
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// Each quadrangle would be returned as a row in the `points` Mat and each point is a Vecf.
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// Returns true as long as some QR code was detected even in case where the decoding failed
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// For usage please see TestQRCodeDetector
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// For further details, please see:
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//https://docs.opencv.org/master/de/dc3/classcv_1_1QRCodeDetector.html#a188b63ffa17922b2c65d8a0ab7b70775
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func (a *QRCodeDetector) DetectAndDecodeMulti(input Mat, decoded *[]string, points *Mat, qrCodes *[]Mat) bool {
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cDecoded := C.CStrings{}
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defer C.CStrings_Close(cDecoded)
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cQrCodes := C.struct_Mats{}
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defer C.Mats_Close(cQrCodes)
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success := C.QRCodeDetector_DetectAndDecodeMulti(a.p, input.p, &cDecoded, points.p, &cQrCodes)
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if !success {
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return bool(success)
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}
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tmpCodes := make([]Mat, cQrCodes.length)
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for i := C.int(0); i < cQrCodes.length; i++ {
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tmpCodes[i].p = C.Mats_get(cQrCodes, i)
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}
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for _, qr := range tmpCodes {
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*qrCodes = append(*qrCodes, qr)
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}
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for _, s := range toGoStrings(cDecoded) {
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*decoded = append(*decoded, s)
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}
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return bool(success)
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}
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