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Like we used cv.drawKeypoints() to draw keypoints, cv.drawMatches() helps us to draw the matches. This function is much faster than the function fillPoly . The idea is to use the line() function from OpenCV C++ library. Thickness of lines used to render the text. There's a tutorial in the official documentation for drawing. . Parameter indicating a contour to draw. Step 2: Determine the variable range. What exactly do you want to achieve? img, text, org, fontFace, fontScale, color[, thickness[, lineType[, bottomLeftOrigin]]]. Maximal level for drawn contours. From this, can the Silencer answer be combined to make the lines long (and not just limited to these two given points) or your answer have a different method ? If you don't want the image closed and want to continue how you started: Regarding your current code, it looks like you are trying to access the next point by indexing the current point. Thickness of the ellipse arc outline, if positive. img3 = cv.drawMatchesKnn(img1,kp1,img2,kp2,good, index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5). What is the difference between Python's list methods append and extend? See getTextSize for a text rendering code example. Next Tutorial: Random generator and text with OpenCV. Optional contour shift parameter. Does a password policy with a restriction of repeated characters increase security? but opencv point is like (561, 168) You can unpack it like you did with the circle and then do the tuple x, y = points [0].ravel () (x,y) or you can use tuple (points [0].ravel ()) or tuple (points [0] [0]) Edit You wanted from one side of the screen to the other one, that is also easy. The boundaries of the shapes can be rendered with antialiasing (implemented only for 8-bit images for now). img, pts, color[, lineType[, shift[, offset]]]. But we need to have those coordinates with us. DMatch.distance - Distance between descriptors. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. The function cv::clipLine calculates a part of the line segment that is entirely within the specified rectangle. Get difference between two lists with Unique Entries, openCV: cannot detect small shapes using findContours. When true, the image data origin is at the bottom-left corner. Draw line $l$. You need to check for the next point in the original array.