You can use cv_image to convert from Mat to dlib image and dlib::toMat to convert from dlib to Mat.
//Mat to dlib image
cv_image<bgr_pixel> dlib_img(mat);
Edit:
As far I know, for n channel Mats you've to provide custom pixel_traits
. For example, for a 5 channel Mat image you can do:
namespace dlib{
struct custom_pixel
{
custom_pixel (
) {}
custom_pixel (
unsigned char c1_,
unsigned char c2_,
unsigned char c3_,
unsigned char c4_,
unsigned char c5_
) : c1(c1_), c2(c2_), c3(c3_), c4(c4_), c5(c5_) {}
unsigned char c1;
unsigned char c2;
unsigned char c3;
unsigned char c4;
unsigned char c5;
};
template <>
struct pixel_traits<custom_pixel>
{
constexpr static bool rgb = false;
constexpr static bool rgb_alpha = false;
constexpr static bool grayscale = false;
constexpr static bool hsi = false;
constexpr static bool lab = false;
enum { num = 5};// provide number of channels here
typedef unsigned char basic_pixel_type; //provide channel depth here
static basic_pixel_type min() { return 0;}
static basic_pixel_type max() { return 255;}
constexpr static bool is_unsigned = true;
constexpr static bool has_alpha = false;
};
}
Then to convert from Mat to dlib and vice versa:
int main(int argc, char** argv)
{
// from opencv to dlib
Mat mat_img = Mat::zeros(3, 3, CV_8UC(5));
cv_image<custom_pixel> dlib_img(mat_img);
//from dlib to opencv
Mat mat_img_new = dlib::toMat(dlib_img);
}