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        "author": "Masahiro Yoshimoto",
        "author_email": "yoshimoto@flab.phys.nagoya-u.ac.jp",
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            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Image Recognition",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Scientific/Engineering :: Physics"
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        "description": "==========\naffine6p\n==========\n\nThe Python affine6p lib is to estimate affine transformation parameters between two sets of 2D points.::\n\n    | x' |   | a  b  p | | x |\n    | y' | = | c  d  q | | y |\n    | 1  |   | 0  0  1 | | 1 |\n\n.. image:: https://gitlab.com/yoshimoto/affine6p-py/raw/master/affine6p.png\n   :alt: Example transformation\n   :height: 398px\n   :width: 342px\n\nWhen the sets are more than three points, the lib estimate parameters with the least squares method.\n\nIn making this lib, I used a lot of ideas in nudged lib. Ref: https://github.com/axelpale/nudged-py\n\nInstall\n-----------\nUse pip::\n\n    pip install affine6p\n\nUsage\n-----------\n\nYou have lists of points for the **original** and **converted** of the transformation function to be estimated::\n\n    import affine6p\n    origin = [[0,0], [1,0], [0,1], [1,1]]\n    convert = [[0,0], [1,0], [0,1], [1,1.1]]\n    trans = affine6p.estimate(origin, convert)\n    trans.get_matrix()\n    # [[1.0, 0.0, 0.0],\n    # [0.050000000000000044, 1.05, -0.02499999999999991],\n    # [0, 0, 1]]\n    affine6p.estimate_error(trans, origin, convert)\n    # 0.025000000000000022\n\nWhen the number of origin is **1**, assume the following relationship::\n\n    a = d = 1 and b = c = 0\n\nWhen the number of origin is **2**, assume the following relationship as described in *estimate_helmert*.::\n\n    a = d and b = -c \n\nYou can access **Transform class members**.::\n\n    trans.a() # params[0]\n    trans.b() # params[1]\n    trans.c() # params[2]\n    trans.d() # params[3]\n    trans.p() # params[4]\n    trans.q() # params[5]\n    trans.get_matrix() # [[a, b, p], [c, d, q], [0, 0, 1]]\n    trans.get_rotation_x() # math.atan2(-b, a)\n    trans.get_rotation_y() # math.atan2(c, d)\n    trans.get_scale_x() # sqrt(a*a + b*b)\n    trans.get_scale_y() # sqrt(c*c + d*d)\n    trans.get_scale() # sqrt((scale_x*scale_x+scale_y*scale_y)*0.5)\n    trans.get_translation() # [p, q]\n    trans.params # [a, b, c, d, p, q]\n\nYou can apply **transform** or **rotate** to 2D point or points. The rotate means *p = q = 0*.::\n\n    trans.transform([0, 0])\n    trans.transform([[0, 0], [1, 1]])\n    point = [0, 0]\n    trans.transform_inv(point)\n    trans.rotate(point)\n    trans.rotate_inv(point)\n\n",
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        "keywords": "calculate affine transformation six parameters",
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