2017-08-04 14:30:54 -0500 commented question findHomography + perspectiveTransform --> exceeds target Rect I wish that all the blue points (SRC) will reside inside the yellow rectangle. Is there a way to obtain that? Desirably, they should get arranged in 3 parallel rows. 2017-08-04 07:59:15 -0500 asked a question findHomography + perspectiveTransform --> exceeds target Rect Hi all, I develop with python, with numpy and openCV (3.1.0). I have a SRC array of 2D points, which I wish to warp into a rectangle region. SRC.T = array([[209 210 239 274 307 337 366 404 427 461 484 489 493] [330 309 339 304 310 332 353 311 348 324 337 317 296]])  I've calculated the required homography (H) as following: H, _ = findHomography(rect_src, rect_dst)  Where: rect_src = array([[209, 282], [209, 330], [484, 337], [493, 296]]) rect_dst = array([[209, 296], [209, 353], [493, 353], [493, 296]])  I got the following homography matrix (which I've verifying manually it makes sense..): H = [[ 5.81755130e-01 -1.21849288e-01 7.21264687e+01] [ -1.46583486e-01 6.99605042e-01 5.90321609e+01] [ -3.49962434e-04 -5.83010949e-04 1.00000000e+00]]  I've then warped the SRC points with the above homography matrix, hoping all SRC points will utilize the rect_dst region: DST = perspectiveTransform(SRC, H).astype(int)  I got the following DST points: DST.T = array([[209 209 236 267 299 330 363 397 429 462 493 493 493] [353 327 363 318 324 351 378 320 370 335 353 324 296]])  Unfortunately, the DST points exceed the rect_dst region, so I didn't get the desired outcome... Attached you may find a debug image, where SRC points are in blue and DST points are in yellow (please ignore the red and the green points). Can you please advise me where did I go wrong and how to obtain the desired feature? Thanks ahead, Shahar C:\fakepath\img_possible_marks_.jpg