# Embedded CV 1. fitElliips 2. findContour precision error a = 0.0000000002328306 # Errors # SVD Good # backsub -21.9216106932838990 -143.0006939375632555 3.8134959448732229 14.4630607975568424 -20.1868153820923730 -21.9216101867994766 -143.0006906336252825 3.8134958567640780 14.4631101619478830 -20.1866507714695196 # fitEllips (double) about 0~8 / 1000000 center = 98.968727 / 44.976013, size = 36.015713 / 92.059372, angle = 90.901993 center = 98.968730 / 44.976014, size = 36.015713 / 92.059373, angle = 90.901993 center = 217.370895 / 77.822464, size = 78.901093 / 133.113312, angle = 179.930923 center = 217.370900 / 77.822467, size = 78.901095 / 133.113313, angle = 179.930921 center = 367.232178 / 78.163750, size = 79.443207 / 132.380798, angle = 134.748199 center = 367.232166 / 78.163751, size = 79.443211 / 132.380800, angle = 134.748197 # fitEllips (float) about 0~15 / 1000000 center = 98.968727 / 44.976013, size = 36.015713 / 92.059372, angle = 90.901993 center = 98.968735 / 44.976013, size = 36.015717 / 92.059372, angle = 90.902000 center = 217.370895 / 77.822464, size = 78.901093 / 133.113312, angle = 179.930923 center = 217.370895 / 77.822464, size = 78.901100 / 133.113327, angle = 179.930923 center = 367.232178 / 78.163750, size = 79.443207 / 132.380798, angle = 134.748199 center = 367.232178 / 78.163750, size = 79.443199 / 132.380798, angle = 134.748215 # findContour CV function: ```=cpp void cv::findContours( InputArray _image, OutputArrayOfArrays _contours, OutputArray _hierarchy, int mode, int method, Point offset ) in contours.cpp ``` current mode = cv2.RETR_TREE current method = cv2.CHAIN_APPROX_TC89_KCOS, cv2.CHAIN_APPROX_NONE # ``` 0. detect_frame 1. check_frame 2. find_pupil_circle_marker 3. find_concentric_circles findContours -> get_nested_clusters -> (node>min)&&(node_num<max) -> fitEllipse -> concentirc + ``` fit accu numpy.sklearn no open source: (最小平方法求解線性方程)http://blog.fens.me/r-lsm-regression/ https://ithelp.ithome.com.tw/articles/10186400 (逆矩陣求法)https://www.codesansar.com/numerical-methods/matrix-inverse-using-gauss-jordan-method-c-program.htm