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import numpy as np
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from scipy.optimize import minimize
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#保存相机内参、外参等参数
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# class Model:
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# def __init__(self):
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# # 内参
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# self.K = np.array([[801.8319, 0, 647.8920],
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# [0, 801.7619, 532],
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# [0, 0, 1]])
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# self.f = 3.6
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# self.H = 1019.0000170167332
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# self.dx = self.f / self.K[0, 0]
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# self.dy = self.f / self.K[1, 1]
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# self.u0 = self.K[0, 2]
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# self.v0 = self.K[1, 2]
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# # 外参
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# self.alpha = 0.7072338025822084
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# self.beta = 0.9077237961986776
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# # 位置修正
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# self.y = -70
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# self.x = 22
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# # 数据截断线
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# self.limit_slope = 0.3259949467095897
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# self.limit_intercept = 452.86565535382374
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class Model:
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def __init__(self):
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# 内参
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# self.K = np.array([[1086.58411235010, 0.00000000e+00, 656.379279306796],
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# [0.00000000e+00, 1086.65442545872, 960-489.101890262552],
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# [0.00000000e+00, 0.00000000e+00, 1.00000000e+00]])
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self.K = np.array([[838.19297892, 0, 658.51580973],
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[0, 836.93529706, 960-484.42225009],
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[0, 0, 1]])
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self.dist_coeffs = [[-4.50688803e-01, 2.60760637e-01, 2.10619624e-04, - 6.69674309e-04, - 4.47846385e-02]]
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self.f = 3.6
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self.H = 1.007e+03-9
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self.dx = self.f / self.K[0, 0]
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self.dy = self.f / self.K[1, 1]
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self.u0 = self.K[0, 2]
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self.v0 = self.K[1, 2]
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# 外参
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# self.alpha = 8.749e-01
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# self.beta = 7.664e-01
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# self.alpha = 9.229e-01
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# self.beta = 8.599e-01
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self.alpha = 9.135e-01
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self.beta = 7.271e-01
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# self.alpha = 8.110e-01
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# self.beta = 8.838e-01
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# 位置修正
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self.y = 0
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self.x = 0
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# 数据截断线
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self.limit_slope = 0.3533327436076127
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self.limit_intercept = 553.8003793475132
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# self.q = -1.524e-01
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self.q = -2.892e-02
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self.gama = 0.5776040711992061
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