Hi AastaLLL, Sorry for late reply,
I tested the klt_tracker algorithm while printing the bbox size on your video test “dashcam.mp4” with the text descriptor containing only “427 562 342 14 16”. Here is the result of bbox descriptor :
Frame number : 464
x : 438.488
y : 353.192
w : 53.0545
h : 60.6337
465 → update 1
Frame number : 465
x : 384.424
y : 366.494
w : 78.185
h : 88.5114
466 → dropped 1
While calculing coordinates as follow :
std::cout << " x : " << bboxes[b].bbox.xform.mat3[0][2] << std::endl;
std::cout << " y : " << bboxes[b].bbox.xform.mat3[1][2] << std::endl;
std::cout << " w : " << bboxes[b].bbox.width * bboxes[b].bbox.xform.mat3[0][0] << std::endl;
std::cout << " h : " << bboxes[b].bbox.height * bboxes[b].bbox.xform.mat3[1][1]<< std::endl;
But this algorithm, unlike the Visionworks object_tracker_nvxcu, return the grayscale image which is not what i want.
I tried to copy the original image and to add bboxes on it, but I have not yet succeeded. My camera is returning images on VPI_IMAGE_FORMAT_BGR8 format. The fonction SaveKLTBoxes() doesn’t support this format.
For now i’m using VisionWorks algorithms because it offers much more possibility. I will learn more details about vpi tonight.