我想把实地的地物点标注到大疆无人机拍摄的照片上，用的是cgcs2000坐标系，我将坐标输入，返回的像素坐标和实际的地物点不能匹配上
import numpy as np
import math
from pyexiv2 import Image
import cv2
#获取了像片拍摄时云台的姿态角
def readJpgXmp(path):
file_name = path
test = Image(file_name)
f = test.read_xmp()
lat = f["Xmp.drone-dji.GpsLatitude"] #纬度
lon = f["Xmp.drone-dji.GpsLongitude"] # 经度
height = f["Xmp.drone-dji.AbsoluteAltitude"] #
roll = f["Xmp.drone-dji.GimbalRollDegree"] #roll
yaw = f["Xmp.drone-dji.GimbalYawDegree"] # yaw
pitch = f["Xmp.drone-dji.GimbalPitchDegree"] # pitch
return float(roll),float(yaw),float(pitch)
#姿态角导入到下面的函数中创建旋转矩阵
def eulerAnglesToRotationMatrix(theta):
# 分别构建三个轴对应的旋转矩阵
R_x = np.array([[1, 0, 0],
[0, math.cos(theta[0]), -math.sin(theta[0])],
[0, math.sin(theta[0]), math.cos(theta[0])]
])
R_y = np.array([[math.cos(theta[1]), 0, math.sin(theta[1])],
[0, 1, 0],
[-math.sin(theta[1]), 0, math.cos(theta[1])]
])
R_z = np.array([[math.cos(theta[2]), -math.sin(theta[2]), 0],
[math.sin(theta[2]), math.cos(theta[2]), 0],
[0, 0, 1]
])
# 将三个矩阵相乘，得到最终的旋转矩阵
R = np.dot(R_z, R_y, R_x)
return R
#计算相机的内参
def neican(pix,size,f):
#8194*5460 #像片的尺寸（像素）
#35.9*24 # cmos的尺寸（毫米）
#35 #焦距（毫米）
u0 = pix[0]/2
v0 = pix[1]/2
dx = size[0]/pix[0]
dy = size[1]/pix[1]
fx = f/dx
fy = f/dy
return np.array([[fx, 0, u0], [0, fy, v0], [0, 0, 1]])
#读取像片的姿态角 roll，yaw，pitch
xmpInfo = readJpgXmp(r'C:\Users\Administrator\Desktop\DJI_20210521160101_0211.JPG')
roll,yaw,pitch = xmpInfo
#旋转矩阵
r = eulerAnglesToRotationMatrix([math.radians(roll),math.radians(pitch),math.radians(yaw)]) #旋转矩阵
print(r)
#平移矩阵
t = np.array([[511914.760791,3372600.750728,231]]).T
#内参矩阵
ins = neican([8194,5460],[35.9,24],35)#内参
#世界坐标系中的地物点
list1 = np.float32([[511914.760791,3372600.750728,0]]) #3d点
#将地物点，旋转矩阵，平移矩阵，内参，传入 cv2.projectPoints（）函数里
result2, _ = cv2.projectPoints(list1,r,t,ins,0)
print(result2)
返回的像素坐标不是我想要对应的地物点，请问是什么原因呢？
