Umeyama
Umeyama is a Python library implementing the Umeyama method for estimating the optimal similarity transformation (rotation, translation, and uniform scaling) between two sets of corresponding points.
pip install umeyama
Quick Start
from umeyama import umeyama
import numpy as np
src = np.array([[0, 0], [1, 0], [1, 1], [0, 1]], dtype=float)
dst = np.array([[1, 1], [1, 2], [2, 2], [2, 1]], dtype=float)
result = umeyama(src, dst)
print(result.rotation) # Rotation matrix
print(result.translation) # Translation vector
print(result.scale) # Scale factor
transformed = result.apply(src)
print(result.rmse(src, dst)) # Root mean square error
References
- Umeyama, Shinji. "Least-Squares Estimation of Transformation Parameters Between Two Point Patterns." IEEE Transactions on Pattern Analysis and Machine Intelligence 13, no. 4 (April 1991): 376–80. https://doi.org/10.1109/34.88573.
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