Trying to work with the Thin Plate Spline warping in python. The actual warping works just fine:
tps = cv2.createThinPlateSplineShapeTransformer()
pts1 = [(10, 10), (100, 100), (50, 100), (200, 30), (60, 20), (150, 200), (120, 90)]
pts2 = [(15, 5), (110, 105), (55, 105), (190, 35), (70, 20), (155, 205), (115, 95)]
cv2.imread("input.png")
matches = [cv2.DMatch(i, i, 0) for i in range(7)]
tps.estimateTransformation(np.array(pts1).reshape((-1, 7, 2)), np.array(pts2).reshape((-1, 7, 2)), matches)
dst = tps.warpImage(img)
cv2.imwrite('warped.png', dst)
The problem seems to be in the applyTransformation. I'd expect that the transform from points in pts1 should lead to points in pts2, but it seems the transform maps all points to a single (wrong) point:
>>> tps.applyTransformation(np.array((10,10)).reshape((-1, 1, 2)))
(7.34408968128264e-05, array([[[ 4.386129 , -6.4083347]]], dtype=float32))
>>> tps.applyTransformation(np.array((100,100)).reshape((-1, 1, 2)))
(7.34408968128264e-05, array([[[ 4.386129 , -6.4083347]]], dtype=float32))
What can be the issue? OpenCV version is 3.4.2.
