typedef struct elem_ { float f1; float f2; } elem; elem data[9] = { 0.0f }; CvMat mat = cvMat(3, 3, CV_32FC2, data ); float f1 = CV_MAT_ELEM(mat, elem, row, col).f1; float f2 = CV_MAT_ELEM(mat, elem, row, col).f2; CV_MAT_ELEM(mat, elem, row, col).f1 = 1212.0f; CV_MAT_ELEM(mat, elem, row, col).f2 = 326.0f; Update : for OpenCV2.0 1. … Read more
I stumbled upon this answer while I was searching for a way to automatically compute Canny’s threshold values. Hope this helps anyone who comes looking for a good method for determining automatic threshold values for Canny’s algorithm… If your image consists of distinct foreground and background, then the edge of foreground object can use extracted … Read more
Contrast and brightness can be adjusted using alpha (α) and beta (β), respectively. These variables are often called the gain and bias parameters. The expression can be written as OpenCV already implements this as cv2.convertScaleAbs() so we can just use this function with user defined alpha and beta values. import cv2 image = cv2.imread(‘1.jpg’) alpha … Read more
If you’re using a recent version of OpenCV, you’re better off avoiding OS-specific methods: vector<string> fn; // std::string in opencv2.4, but cv::String in 3.0 string path = “e:/code/vlc/faces2/*.png”; cv::glob(path,fn,false); // Now you got a list of filenames in fn. (Ohh, and again, avoid deprecated C-API functions like cvLoad like hell, please!!)
If you remove the alpha channel, you will see that the background of the template is a dark green. So it will only match the dark background squares. You are reading the template with alpha, but the alpha channel will not be used in the template matching. You need to extract the alpha channel of … Read more
OpenCV doesn’t have a skeleton function, but you can make your own function. From here: The skeleton/MAT can be produced in two main ways. The first is to use some kind of morphological thinning that successively erodes away pixels from the boundary (while preserving the end points of line segments) until no more thinning is … Read more
For easy and simple way using COCO dataset, follow these steps : Modify (or copy for backup) the coco.names file in darknet\data\coco.names Delete all other classes except car Modify your cfg file (e.g. yolov3.cfg), change the 3 classes on line 610, 696, 783 from 80 to 1 Change the 3 filters in cfg file on … Read more
This approach works only on points. You don’t need to create masks for this. The main idea is: Find defects on contour If I find at least two defects, find the two closest defects Remove from the contour the points between the two closest defects Restart from 1 on the new contour I get the … Read more
For those on Windows who don’t want to mess with building OpenCV 3.0 from source, Christoph Gohlke maintains Windows binaries for many Python packages, including OpenCV 3.0 with Python 3.x bindings! See here: http://www.lfd.uci.edu/~gohlke/pythonlibs/#opencv To install, just download the 64-bit or 32-bit .whl file appropriate for your system, then run pip install [filename]. Then the … Read more
“The reason why the early developers at OpenCV chose BGR color format is probably that back then BGR color format was popular among camera manufacturers and software providers. E.g. in Windows, when specifying color value using COLORREF they use the BGR format 0x00bbggrr. BGR was a choice made for historical reasons and now we have … Read more