2020-04-11 03:11:39 -0600 | received badge | ● Teacher (source) |
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2017-02-02 17:47:12 -0600 | asked a question | xphoto/ color balance sample - problem with learn_color_balance.py Hi, I am trying to make the color balance sample (opencv extra modules, rebuilt from opencv 3.x head) working. but I have no luck while running the learn_color_balance.py python script, as I get:
I am not using python usually, so it might be a configuration problem I suppose. any help appreciated. |
2014-02-18 12:35:43 -0600 | commented question | Watershed on gray image I agree this is annoying - even if you can add 2 dummy channels. |
2014-02-18 11:43:26 -0600 | answered a question | Is it normal a HSV image looks like this? Bah..they do not look like the original picture because you display the HSV as if it was RGB that's all. But HSV is a better model to 'separate' perceptually the colors (then separate your objects). once your objects are separated, apply inverse color conversion to get the original color. |
2013-12-12 18:08:02 -0600 | answered a question | Finding homography matrix I see nothing obvious wrong with your code RANSAC tries to find an homography given a set of matches, and use a probalistic algorihm, sometimes it gives bad homographies, you need reject them and retry... (see "good result or bad result for findHomography" post). |
2013-12-12 17:48:26 -0600 | received badge | ● Editor (source) |
2013-12-12 17:44:14 -0600 | answered a question | good result or bad result for findHomography My understanding concerning :
Compute the determinant of the top left 2x2 homography matrix, and check if it's "too close" to zero for comfort...btw you can also check if it's *too *far from zero because then the invert matrix would have a determinant too close to zero. A determinant of zero would mean the matrix is not inversible, too close to zero would mean *singular (like you see the plane object at 90°, which is almost impossible if you use *good matches). const double det = H.at<double>(0, 0) * H.at<double>(1, 1) - H.at<double>(1, 0) * H.at<double>(0, 1); One way to do it would be to specify a positive value, higher than 1, say N, and then: if((fabs(det)>(double)N) || (fabs(det)<(1.0/(double)N)) return false; // bad homography And while we are at it...if det<0 the homography is not conserving the orientation (clockwise<->anticlockwise), except if you are watching the object in a mirror...it is certainly not good (plus the sift/surf descriptors are not done to be mirror invariants as far as i know, so you would probably don'thave good maches). if(det<0) return false; // no mirrors in the scene /* for reading & reference : [Detecting Planar Homographies in an Image Pair Etienne Vincent and Robert Laganiere School of Information Technology and Engineering University of Ottawa Canada K1N 6N5] */ |