import numpy as np
import cv2
# 畸變校正
def undistort_pixel(pixel_x, pixel_y, sym_dist, dec_dist):
    k0,k1,k2,k3=sym_dist
    # k1, k2, p1, p2, k3 = sym_dist
    p1,p2,p3=dec_dist
    fx = focal_length_mm
    fy = focal_length_mm
    cx = xpoff_px
    cy = ypoff_px
    distCoeffs = np.array([k1, k2, p1, p2,k3])
    cameraMatrix = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]])
    distorted_points = np.array([[pixel_x, pixel_y]], dtype=np.float32)
    undistorted_points = cv2.undistortPoints(distorted_points, cameraMatrix, distCoeffs)
    #################################################### 4\對圖像去畸變
    img = cv2.imread('./images/100_0004_0001.JPG')
    img_undistored = cv2.undistort(img, cameraMatrix, distCoeffs)
    cv2.imwrite('./images/100_0004_00011.JPG', img_undistored)
    return undistorted_points[0][0][0], undistorted_points[0][0][1]
# 相機坐標轉(zhuǎn)世界坐標
def camera_to_world_coordinates(cam_coords, pos):
    # 獲取相機到世界的轉(zhuǎn)換參數(shù)
    pos_x, pos_y, pos_z, roll, pitch, yaw = pos
    # 將角度轉(zhuǎn)換為弧度
    roll = np.radians(roll)
    pitch = np.radians(pitch)
    yaw = np.radians(yaw)
    # 計算旋轉(zhuǎn)矩陣
    R_roll = np.array([
        [1, 0, 0],
        [0, np.cos(roll), -np.sin(roll)],
        [0, np.sin(roll), np.cos(roll)]
    ])
    R_pitch = np.array([
        [np.cos(pitch), 0, np.sin(pitch)],
        [0, 1, 0],
        [-np.sin(pitch), 0, np.cos(pitch)]
    ])
    R_yaw = np.array([
        [np.cos(yaw), -np.sin(yaw), 0],
        [np.sin(yaw), np.cos(yaw), 0],
        [0, 0, 1]
    ])
    R = R_yaw @ R_pitch @ R_roll
    # 相機坐標轉(zhuǎn)換到世界坐標
    cam_coords_homogeneous = np.array([cam_coords[0], cam_coords[1], -H, 1])
    world_coords = R @ cam_coords_homogeneous[:3] + np.array([pos_x, pos_y, pos_z])
    return world_coords
if __name__ == "__main__":
    ####################################################基本參數(shù)
    # 傳感器寬度和高度（毫米）
    sensor_width_mm = 12.83331744000000007588
    sensor_height_mm = 8.55554496000000064271
    # 圖像寬度和高度（像素）
    image_width_px = 5472
    image_height_px = 3648
    # 焦距（毫米）
    focal_length_mm = 8.69244671863242679422
    # 焦距（米）
    focal_length_m = 8.69244671863242679422/1000
    # 相對航高（米）
    H=86.93
    #像主點坐標 （像素）
    xpoff_px=20.88973563438230485190
    ypoff_px=50.51977022866981315019
    #################################################### 1\計算空間分辨率
    # 傳感器尺寸轉(zhuǎn)換為米
    sensor_width_m = sensor_width_mm / 1000
    sensor_height_m = sensor_height_mm / 1000
    # 計算水平和垂直的 GSD
    GSD_x = (sensor_width_m/image_width_px) * (H / focal_length_m )
    GSD_y = (sensor_height_m /image_height_px) * (H / focal_length_m)
    # 水平和垂直方向的 GSD
    print("水平方向的 GSD:", GSD_x, "米/像素")
    print("垂直方向的 GSD:", GSD_y, "米/像素")
    #################################################### 2\給定像素坐標,計算相機坐標
    # 像素坐標
    oripixel_x = image_width_px
    oripixel_y = image_height_px
    # oripixel_x = image_width_px/2
    # oripixel_y = image_height_px/2
    # oripixel_x = 0
    # oripixel_y = 0
    pixel_x=oripixel_x-xpoff_px-image_width_px/2
    pixel_y=oripixel_y-ypoff_px-image_height_px/2
    # 計算相機坐標（假設無畸變）
    camera_x = pixel_x * GSD_x
    camera_y = pixel_y * GSD_y
    print("像素坐標 (", oripixel_x, ",", oripixel_y, ") 對應的相機坐標 (x, y): (", camera_x, "米, ", camera_y, "米)")
    #################################################### 3\計算畸變后坐標
    # 對稱畸變系數(shù)
    sym_dist = [0, -0.00043396118129128110, 0.00000262222711982075, -0.00000001047488706013]
    # 徑向畸變
    dec_dist = [0.00000205885592671873, -0.00000321714140091248, 0]
    # 進行畸變校正
    undistorted_camera_x, undistorted_camera_y = undistort_pixel(pixel_x, pixel_y, sym_dist, dec_dist)
    print("畸變校正后像素坐標 (", oripixel_x, ",", oripixel_y, ") 對應的相機坐標 (x, y): (", undistorted_camera_x, "米, ", undistorted_camera_y, "米)")
    #################################################### 4\計算世界坐標
    # POS數(shù)據(jù)
    pos = [433452.054688, 2881728.519704, 183.789696, 0.648220, -0.226028, 14.490357]
    # 計算世界坐標
    world_coords = camera_to_world_coordinates((undistorted_camera_x, undistorted_camera_y), pos)
    print("旋轉(zhuǎn)平移變換后像素坐標 (", oripixel_x, ",", oripixel_y, ") 對應的世界坐標 (x, y): (", world_coords[0], "米, ", world_coords[1], "米)")