J'étais coincé dans le même problème il y a quelques semaines, j'ai trouvé un script python qui peut aider. Solution originale d' ici
import pyproj
import math
import numpy as np
from statistics import mean
import scipy.optimize as optimize
#This function converts the numbers into text
def text_2_CRS(params):
# print(params) # <-- you'll see that params is a NumPy array
x_0, y_0, gamma, alpha, lat_0, lonc = params # <-- for readability you may wish to assign names to the component variables
pm = '+proj=omerc +lat_0='+ str(lat_0) +' +lonc='+ str(lonc) +' +alpha=' + str(alpha) + ' +gamma=' + str(
gamma) + ' +k=0.999585495 +x_0=' + str(x_0) + ' +y_0=' + str(y_0) + ' +ellps=GRS80 +units=m +no_defs'
return pm
#Optimisation function
def convert(params):
pm = text_2_CRS(params)
trans_points = []
#Put your control points in mine grid coordinates here
points_local = [[5663.648, 7386.58],
[20265.326, 493.126],
[1000, -10000],
[-1000, -10000],
[1331.817, 2390.206],
[5794, -1033.6],
]
# Put your control points here mga here
points_mga = [[567416.145863305, 7434410.3451835],
[579090.883705669, 7423265.25196681],
[557507.390559793, 7419390.6658927],
[555610.407664593, 7420021.64968145],
[561731.125709093, 7431037.98474379],
[564883.285081307, 7426382.75146683],
]
for i in range(len(points_local)):
#note that EPSG:28350 is MGA94 Zone 50
trans = pyproj.transform(pyproj.Proj(pm), pyproj.Proj("EPSG:28350"), points_local[i][0], points_local[i][1])
trans_points.append(trans)
error = []
#this finds the difference between the control points
for i in range(len(points_mga)):
x1 = trans_points[i][0]
y1 = trans_points[i][1]
x2 = points_mga[i][0]
y2 = points_mga[i][1]
error.append(math.sqrt((x1 - x2) ** 2 + (y1 - y2) ** 2))
print("Current Params are: ")
with np.printoptions(precision=3, suppress=True):
print(params)
print("Current average error is: " + str(mean(error)) + " meters")
print("String to use is: " + pm)
print('')
return mean(error)
#Add your inital guess
x_0 = 950
y_0 = -1200
gamma = -18.39841101
alpha=-0
lat_0 = -23.2583926082939
lonc = 117.589084840039
#define your control points
points_local = [[5663.648,7386.58],
[20265.326,493.126],
[1000,-10000],
[-1000,-10000],
[1331.817,2390.206],
[5794,-1033.6],
]
points_mga = [[567416.145863305,7434410.3451835],
[579090.883705669,7423265.25196681],
[557507.390559793,7419390.6658927],
[555610.407664593,7420021.64968145],
[561731.125709093,7431037.98474379],
[564883.285081307,7426382.75146683],
]
params = [x_0, y_0, gamma,alpha, lat_0, lonc]
error = convert(params)
print(error)
result = optimize.minimize(convert, params, method='Powell')
if result.success:
fitted_params = result.x
print(fitted_params)
else:
raise ValueError(result.message)