228 lines
8.6 KiB
Go
228 lines
8.6 KiB
Go
package gocv
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/*
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#include <stdlib.h>
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#include "photo.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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//SeamlessCloneFlags seamlessClone algorithm flags
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type SeamlessCloneFlags int
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// MergeMertens is a wrapper around the cv::MergeMertens.
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type MergeMertens struct {
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p unsafe.Pointer // This unsafe pointer will in fact be a C.MergeMertens
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}
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// AlignMTB is a wrapper around the cv::AlignMTB.
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type AlignMTB struct {
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p unsafe.Pointer // This unsafe pointer will in fact be a C.AlignMTB
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}
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const (
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// NormalClone The power of the method is fully expressed when inserting objects with complex outlines into a new background.
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NormalClone SeamlessCloneFlags = iota
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// MixedClone The classic method, color-based selection and alpha masking might be time consuming and often leaves an undesirable halo. Seamless cloning, even averaged with the original image, is not effective. Mixed seamless cloning based on a loose selection proves effective.
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MixedClone
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// MonochromeTransfer Monochrome transfer allows the user to easily replace certain features of one object by alternative features.
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MonochromeTransfer
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)
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// ColorChange mix two differently colored versions of an image seamlessly.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/df/da0/group__photo__clone.html#ga6684f35dc669ff6196a7c340dc73b98e
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//
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func ColorChange(src, mask Mat, dst *Mat, red_mul, green_mul, blue_mul float32) {
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C.ColorChange(src.p, mask.p, dst.p, C.float(red_mul), C.float(green_mul), C.float(blue_mul))
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}
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// SeamlessClone blend two image by Poisson Blending.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/df/da0/group__photo__clone.html#ga2bf426e4c93a6b1f21705513dfeca49d
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//
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func SeamlessClone(src, dst, mask Mat, p image.Point, blend *Mat, flags SeamlessCloneFlags) {
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cp := C.struct_Point{
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x: C.int(p.X),
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y: C.int(p.Y),
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}
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C.SeamlessClone(src.p, dst.p, mask.p, cp, blend.p, C.int(flags))
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}
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// IlluminationChange modifies locally the apparent illumination of an image.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/df/da0/group__photo__clone.html#gac5025767cf2febd8029d474278e886c7
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//
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func IlluminationChange(src, mask Mat, dst *Mat, alpha, beta float32) {
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C.IlluminationChange(src.p, mask.p, dst.p, C.float(alpha), C.float(beta))
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}
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// TextureFlattening washes out the texture of the selected region, giving its contents a flat aspect.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/df/da0/group__photo__clone.html#gad55df6aa53797365fa7cc23959a54004
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//
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func TextureFlattening(src, mask Mat, dst *Mat, lowThreshold, highThreshold float32, kernelSize int) {
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C.TextureFlattening(src.p, mask.p, dst.p, C.float(lowThreshold), C.float(highThreshold), C.int(kernelSize))
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}
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// FastNlMeansDenoisingColoredMulti denoises the selected images.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d1/d79/group__photo__denoise.html#gaa501e71f52fb2dc17ff8ca5e7d2d3619
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//
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func FastNlMeansDenoisingColoredMulti(src []Mat, dst *Mat, imgToDenoiseIndex int, temporalWindowSize int) {
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cMatArray := make([]C.Mat, len(src))
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for i, r := range src {
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cMatArray[i] = (C.Mat)(r.p)
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}
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matsVector := C.struct_Mats{
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mats: (*C.Mat)(&cMatArray[0]),
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length: C.int(len(src)),
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}
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C.FastNlMeansDenoisingColoredMulti(matsVector, dst.p, C.int(imgToDenoiseIndex), C.int(temporalWindowSize))
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}
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// FastNlMeansDenoisingColoredMulti denoises the selected images.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d1/d79/group__photo__denoise.html#gaa501e71f52fb2dc17ff8ca5e7d2d3619
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//
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func FastNlMeansDenoisingColoredMultiWithParams(src []Mat, dst *Mat, imgToDenoiseIndex int, temporalWindowSize int, h float32, hColor float32, templateWindowSize int, searchWindowSize int) {
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cMatArray := make([]C.Mat, len(src))
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for i, r := range src {
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cMatArray[i] = (C.Mat)(r.p)
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}
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matsVector := C.struct_Mats{
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mats: (*C.Mat)(&cMatArray[0]),
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length: C.int(len(src)),
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}
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C.FastNlMeansDenoisingColoredMultiWithParams(matsVector, dst.p, C.int(imgToDenoiseIndex), C.int(temporalWindowSize), C.float(h), C.float(hColor), C.int(templateWindowSize), C.int(searchWindowSize))
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}
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// NewMergeMertens returns returns a new MergeMertens white LDR merge algorithm.
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// of type MergeMertens with default parameters.
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// MergeMertens algorithm merge the ldr image should result in a HDR image.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d6/df5/group__photo__hdr.html
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// https://docs.opencv.org/master/d7/dd6/classcv_1_1MergeMertens.html
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// https://docs.opencv.org/master/d6/df5/group__photo__hdr.html#ga79d59aa3cb3a7c664e59a4b5acc1ccb6
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//
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func NewMergeMertens() MergeMertens {
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return MergeMertens{p: unsafe.Pointer(C.MergeMertens_Create())}
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}
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// NewMergeMertensWithParams returns a new MergeMertens white LDR merge algorithm
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// of type MergeMertens with customized parameters.
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// MergeMertens algorithm merge the ldr image should result in a HDR image.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d6/df5/group__photo__hdr.html
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// https://docs.opencv.org/master/d7/dd6/classcv_1_1MergeMertens.html
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// https://docs.opencv.org/master/d6/df5/group__photo__hdr.html#ga79d59aa3cb3a7c664e59a4b5acc1ccb6
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//
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func NewMergeMertensWithParams(contrast_weight float32, saturation_weight float32, exposure_weight float32) MergeMertens {
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return MergeMertens{p: unsafe.Pointer(C.MergeMertens_CreateWithParams(C.float(contrast_weight), C.float(saturation_weight), C.float(exposure_weight)))}
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}
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// Close MergeMertens.
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func (b *MergeMertens) Close() error {
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C.MergeMertens_Close((C.MergeMertens)(b.p)) // Here the unsafe pointer is cast into the right type
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b.p = nil
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return nil
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}
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// BalanceWhite computes merge LDR images using the current MergeMertens.
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// Return a image MAT : 8bits 3 channel image ( RGB 8 bits )
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// For further details, please see:
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// https://docs.opencv.org/master/d7/dd6/classcv_1_1MergeMertens.html#a2d2254b2aab722c16954de13a663644d
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//
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func (b *MergeMertens) Process(src []Mat, dst *Mat) {
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cMatArray := make([]C.Mat, len(src))
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for i, r := range src {
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cMatArray[i] = (C.Mat)(r.p)
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}
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// Conversion function from a Golang slice into an array of matrices that are understood by OpenCV
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matsVector := C.struct_Mats{
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mats: (*C.Mat)(&cMatArray[0]),
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length: C.int(len(src)),
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}
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C.MergeMertens_Process((C.MergeMertens)(b.p), matsVector, dst.p)
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// Convert a series of double [0.0,1.0] to [0,255] with Golang
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dst.ConvertToWithParams(dst, MatTypeCV8UC3, 255.0, 0.0)
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}
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// NewAlignMTB returns an AlignMTB for converts images to median threshold bitmaps.
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// of type AlignMTB converts images to median threshold bitmaps (1 for pixels
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// brighter than median luminance and 0 otherwise) and than aligns the resulting
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// bitmaps using bit operations.
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// For further details, please see:
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// https://docs.opencv.org/master/d6/df5/group__photo__hdr.html
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// https://docs.opencv.org/master/d7/db6/classcv_1_1AlignMTB.html
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// https://docs.opencv.org/master/d6/df5/group__photo__hdr.html#ga2f1fafc885a5d79dbfb3542e08db0244
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//
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func NewAlignMTB() AlignMTB {
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return AlignMTB{p: unsafe.Pointer(C.AlignMTB_Create())}
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}
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// NewAlignMTBWithParams returns an AlignMTB for converts images to median threshold bitmaps.
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// of type AlignMTB converts images to median threshold bitmaps (1 for pixels
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// brighter than median luminance and 0 otherwise) and than aligns the resulting
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// bitmaps using bit operations.
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// For further details, please see:
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// https://docs.opencv.org/master/d6/df5/group__photo__hdr.html
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// https://docs.opencv.org/master/d7/db6/classcv_1_1AlignMTB.html
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// https://docs.opencv.org/master/d6/df5/group__photo__hdr.html#ga2f1fafc885a5d79dbfb3542e08db0244
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//
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func NewAlignMTBWithParams(max_bits int, exclude_range int, cut bool) AlignMTB {
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return AlignMTB{p: unsafe.Pointer(C.AlignMTB_CreateWithParams(C.int(max_bits), C.int(exclude_range), C.bool(cut)))}
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}
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// Close AlignMTB.
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func (b *AlignMTB) Close() error {
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C.AlignMTB_Close((C.AlignMTB)(b.p))
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b.p = nil
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return nil
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}
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// Process computes an alignment using the current AlignMTB.
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//
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// For further details, please see:
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// https://docs.opencv.org/master/d7/db6/classcv_1_1AlignMTB.html#a37b3417d844f362d781f34155cbcb201
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//
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func (b *AlignMTB) Process(src []Mat, dst *[]Mat) {
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cSrcArray := make([]C.Mat, len(src))
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for i, r := range src {
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cSrcArray[i] = r.p
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}
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cSrcMats := C.struct_Mats{
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mats: (*C.Mat)(&cSrcArray[0]),
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length: C.int(len(src)),
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}
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cDstMats := C.struct_Mats{}
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C.AlignMTB_Process((C.AlignMTB)(b.p), cSrcMats, &cDstMats)
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// Pass the matrices by reference from an OpenCV/C++ to a GoCV::Mat object
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for i := C.int(0); i < cDstMats.length; i++ {
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var tempdst Mat
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tempdst.p = C.Mats_get(cDstMats, i)
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*dst = append(*dst, tempdst)
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}
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return
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}
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