To calculate affine transformation parameters with six free parameters.
Project description
The Python lib to estimate affine transformation parameters between two sets of 2D points.:
| x' | | a b p | | x | | y' | = | c d q | | y | | 1 | | 0 0 1 | | 1 |
When the sets are more than three points, the lib estimate parameters with the least squares method.
In making this lib, I used a lot of ideas in nudged lib. Ref: https://github.com/axelpale/nudged-py
Install
Use pip:
pip install affine6p
Usage
You have lists of points for the original and converted of the transformation function to be estimated:
import affine6p origin = [[0,0], [1,0], [0,1], [1,1]] convert = [[0,0], [1,0], [0,1], [1,1.1]] trans = affine6p.estimate(origin, convert) trans.get_matrix() # [[1.0, 0.0, 0.0], # [0.050000000000000044, 1.05, -0.02499999999999991], # [0, 0, 1]] affine6p.estimate_error(trans, origin, convert) # 0.025000000000000022
When the number of origin is 1, assume the following relationship:
a = d = 1 and b = c = 0
When the number of origin is 2, assume the following relationship as described in estimate_helmert.:
a = d and b = -c
You can access Transform class members.:
trans.a() # params[0] trans.b() # params[1] trans.c() # params[2] trans.d() # params[3] trans.p() # params[4] trans.q() # params[5] trans.get_matrix() # [[a, b, p], [c, d, q], [0, 0, 1]] trans.get_rotation_x() # math.atan2(-b, a) trans.get_rotation_y() # math.atan2(c, d) trans.get_scale_x() # sqrt(a*a + b*b) trans.get_scale_y() # sqrt(c*c + d*d) trans.get_scale() # sqrt((scale_x*scale_x+scale_y*scale_y)*0.5) trans.get_translation() # [p, q] trans.params # [a, b, c, d, p, q]
You can apply transform or rotate to 2D point or points. The rotate means p = q = 0.:
trans.transform([0, 0]) trans.transform([[0, 0], [1, 1]]) point = [0, 0] trans.transform_inv(point) trans.rotate(point) trans.rotate_inv(point)
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