https://github.com/Dongvdong/v1_1_slam_tool
链接:https://pan.baidu.com/s/1vQ-GMFRO9iiLUJCUL2sdEQ?pwd=x8pk
提取码:x8pk
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 | ''' gnss 和 enu 坐标系相互转化 ''' import numpy as np from pyproj import Proj, Transformer import pyproj import math from API_1GetGpsFromIMG import * use_cgcs2000Towgs84 = 0 # 大疆采集的rtk默认坐标系是cgcs2000Towgs84 是否需要转化 貌似转化没啥区别 # # WGS-84定义的常数,用于CGCS2000系统(与WGS-84非常接近) # 1-1 def Api_cgcs2000Towgs84(Gnss_in): # 定义CGCS2000和WGS-84坐标系 cgcs2000 = Proj( 'epsg:4490' ) # CGCS2000的EPSG代码 wgs84 = Proj( 'epsg:4326' ) # WGS-84的EPSG代码 # 使用Transformer进行转换 transformer = Transformer.from_proj(cgcs2000, wgs84, always_xy = True ) # 示例坐标(经度, 纬度, 高度) #lon, lat, h = 116.391, 39.907, 50.0 # 高度为50米 lon, lat, h = Gnss_in[ 1 ], Gnss_in[ 0 ], Gnss_in[ 2 ] # 高度为50米 Gnss_out = [ - 1 , - 1 , - 1 ] # 进行坐标转换 x, y, z = transformer.transform(lon, lat, h) Gnss_out = [y,x,z] #print(f"输入 CGCS2000坐标: 经度={lon}, 纬度={lat}, 高度={h}") #print(f"输出 WGS-84坐标: 经度={x}, 纬度={y}, 高度={z}") return Gnss_out # 1-2 def Api_wgs84Tocgcs2000(Gnss_in): # 定义CGCS2000和WGS-84坐标系 cgcs2000 = Proj( 'epsg:4490' ) # CGCS2000的EPSG代码 wgs84 = Proj( 'epsg:4326' ) # WGS-84的EPSG代码 # 使用Transformer进行转换 transformer = Transformer.from_proj(wgs84,cgcs2000 , always_xy = True ) # 示例坐标(经度, 纬度, 高度) #lon, lat, h = 116.391, 39.907, 50.0 # 高度为50米 lon, lat, h = Gnss_in[ 1 ], Gnss_in[ 0 ], Gnss_in[ 2 ] # 高度为50米 # 进行坐标转换 x, y, z = transformer.transform(lon, lat, h) Gnss_out = [y,x,z] #print(f"输入 WGS-84坐标: 经度={x}, 纬度={y}, 高度={z}") #print(f"输出 CGCS2000坐标: 经度={lon}, 纬度={lat}, 高度={h}") return Gnss_out #============================================================= # WGS-84定义的常数,用于CGCS2000系统(与WGS-84非常接近) a = 6378137.0 # 长半轴(单位:米) b = 6356752.3142 #f = (a - b) / a f = 1 / 298.257223563 # 扁率 CGCS2000系统 #f = 1 / 298.257223565 # 扁率 WGS-84 e2 = 2 * f - f * * 2 # 第一偏心率的平方 pi = 3.14159265359 # 2-1-1 gps转换到ecef def gnss_to_ecef(lat, lon, h): """将地理坐标(经度、纬度、高程)转换为ECEF坐标系""" lat = np.radians(lat) lon = np.radians(lon) N = a / np.sqrt( 1 - e2 * np.sin(lat) * * 2 ) X = (N + h) * np.cos(lat) * np.cos(lon) Y = (N + h) * np.cos(lat) * np.sin(lon) Z = (N * ( 1 - e2) + h) * np.sin(lat) return X, Y, Z # 2-1-2 gps转换到ecef def gnss_to_ecef1(lat_ref,lon_ref,h_ref): transformer = pyproj.Transformer.from_crs( { "proj" : 'latlong' , "ellps" : 'WGS84' , "datum" : 'WGS84' }, { "proj" : 'geocent' , "ellps" : 'WGS84' , "datum" : 'WGS84' }, ) x_ref, y_ref, z_ref = transformer.transform(lon_ref, lat_ref, h_ref ,radians = False ) to_ecef = [x_ref,y_ref,z_ref] return to_ecef #2-2 ''' 功能: # 大地坐标系ECEF转化到gps 输入: 等待转换的ecef 坐标 x, y, z 输出: GPS 坐标 lat, lon, h ''' def ecef_to_gnss(x, y, z): x = float (x) y = float (y) z = float (z) # Convert from ECEF cartesian coordinates to # latitude, longitude and height. WGS-84 x2 = x * * 2 y2 = y * * 2 z2 = z * * 2 #a = 6378137.0000 # earth radius in meters #b = 6356752.3142 # earth semiminor in meters e = math.sqrt ( 1 - (b / a) * * 2 ) b2 = b * b e2 = e * * 2 ep = e * (a / b) r = math.sqrt(x2 + y2) r2 = r * r E2 = a * * 2 - b * * 2 F = 54 * b2 * z2 G = r2 + ( 1 - e2) * z2 - e2 * E2 c = (e2 * e2 * F * r2) / (G * G * G) s = ( 1 + c + math.sqrt(c * c + 2 * c) ) * * ( 1 / 3 ) P = F / ( 3 * (s + 1 / s + 1 ) * * 2 * G * G) Q = math.sqrt( 1 + 2 * e2 * e2 * P) ro = - (P * e2 * r) / ( 1 + Q) + math.sqrt((a * a / 2 ) * ( 1 + 1 / Q) - (P * ( 1 - e2) * z2) / (Q * ( 1 + Q)) - P * r2 / 2 ) tmp = (r - e2 * ro) * * 2 U = math.sqrt( tmp + z2 ) V = math.sqrt( tmp + ( 1 - e2) * z2 ) zo = (b2 * z) / (a * V) height = U * ( 1 - b2 / (a * V) ) lat = math.atan( (z + ep * ep * zo) / r ) temp = math.atan(y / x) if x > = 0 : long = temp elif (x < 0 ) & (y > = 0 ): long = pi + temp else : long = temp - pi lat0 = lat / (pi / 180 ) lon0 = long / (pi / 180 ) h0 = height return lat0, lon0, h0 def ecef_to_gnss_1(x,y,z): transformer = pyproj.Transformer.from_crs( { "proj" : 'geocent' , "ellps" : 'WGS84' , "datum" : 'WGS84' }, { "proj" : 'latlong' , "ellps" : 'WGS84' , "datum" : 'WGS84' }, ) lon, lat, h = transformer.transform(x, y, z ) to_gnss = [lat,lon, h] #print(f"从 ENU坐标: 东={east}, 北={north}, 高={up}") #print(f"转换后的CGCS2000坐标: 纬度={lat}, 经度={lon}, 高度={h}") return to_gnss # 3-1 ecef转换到enu ''' 功能: # 大地坐标系 转化到GPS第一帧为原点的本地ENU坐标系 输入: 等待转换的ecef 坐标 x, y, z 作为原点的GPS第一帧 坐标lat0, lon0, h0 输出: 本地第一帧GPS为原点的 ENU 坐标系 xEast, yNorth, zUp ''' def ecef_to_enu(X, Y, Z, lat_ref, lon_ref, h_ref): """将ECEF坐标转换为ENU坐标""" # 参考点的ECEF坐标 Xr, Yr, Zr = gnss_to_ecef(lat_ref, lon_ref, h_ref) # ECEF到ENU的旋转矩阵 lat_ref = np.radians(lat_ref) lon_ref = np.radians(lon_ref) R = np.array([ [ - np.sin(lon_ref), np.cos(lon_ref), 0 ], [ - np.sin(lat_ref) * np.cos(lon_ref), - np.sin(lat_ref) * np.sin(lon_ref), np.cos(lat_ref)], [np.cos(lat_ref) * np.cos(lon_ref), np.cos(lat_ref) * np.sin(lon_ref), np.sin(lat_ref)] ]) # ECEF坐标差 dX = X - Xr dY = Y - Yr dZ = Z - Zr # 计算ENU坐标 enu = R @ np.array([dX, dY, dZ]) return enu # 3-2 enu转换到ecef ''' 功能: enu坐标转化到ecef坐标 输入: 等待转换的ENU坐标 坐标 xEast, yNorth, zUp GPS第一帧原点 坐标 lat0, lon0, h0 输出: ecef 坐标 x, y, z ''' def enu_to_ecef(east, north, up, lat_ref, lon_ref, h_ref): # 1 参考GNSS点 转化到ecef # 定义参考点的CGCS2000坐标(经度, 纬度, 高度) #lon_ref, lat_ref, h_ref = 116.391, 39.907, 50.0 # 示例参考点 ref_ecef = gnss_to_ecef(lat_ref,lon_ref,h_ref) ecef_x_ref = ref_ecef[ 0 ] ecef_y_ref = ref_ecef[ 1 ] ecef_z_ref = ref_ecef[ 2 ] # 2 等待转换的enu点变换到到ecef坐标系下相对位移 # 将参考点的地理坐标转换为弧度 lat_ref = np.radians(lat_ref) lon_ref = np.radians(lon_ref) # ENU到ECEF的旋转矩阵 R = np.array([ [ - np.sin(lon_ref), np.cos(lon_ref), 0 ], [ - np.sin(lat_ref) * np.cos(lon_ref), - np.sin(lat_ref) * np.sin(lon_ref), np.cos(lat_ref)], [np.cos(lat_ref) * np.cos(lon_ref), np.cos(lat_ref) * np.sin(lon_ref), np.sin(lat_ref)] ]) # 将ENU坐标转换为ECEF坐标 # 定义ENU坐标(East, North, Up) #east, north, up = 100, 200, 30 # 示例ENU坐标 enu_vector = np.array([east, north, up]) ecef_vector = R.T @ enu_vector # 使用矩阵转置进行旋转 # 将ECEF坐标添加到参考点的ECEF坐标 x = ecef_x_ref + ecef_vector[ 0 ] y = ecef_y_ref + ecef_vector[ 1 ] z = ecef_z_ref + ecef_vector[ 2 ] return x,y,z # 4-1 将一个gps转换到enu ''' 功能: # gps直接转化到enu坐标系 相对于指定GPS_ref为原点(一般都是第一帧)的enu坐标系 输入: gnss_in 等待转换的GPS 坐标 lat, lon, h gnss_ref 参考原点GPS 坐标 lat_ref, lon_ref, h_ref 输出: enu坐标 x, y, z ''' def API_gnss_to_enu(gnss_in, gnss_ref): lat = gnss_in[ 0 ] lon = gnss_in[ 1 ] alt = gnss_in[ 2 ] x, y, z = gnss_to_ecef(lat, lon, alt) #x1, y2, z3 = gnss_to_ecef1(lat, lon, alt) lat0 = gnss_ref[ 0 ] lon0 = gnss_ref[ 1 ] alt0 = gnss_ref[ 2 ] e,n,u = ecef_to_enu(x, y, z, lat0, lon0, alt0) #print(f"ENU coordinates: E={e}, N={n}, U={u}") return e,n,u ''' # 原始gnss输入 名字 纬度 经度 高度 DJI_0002.JPG 34.032505638888885 108.76779925 514.638 DJI_0005.JPG 34.03267641666667 108.76781155555555 514.464 DJI_0011.JPG 34.03394725 108.76789833333333 514.635 转化为 纬度 经度 高度 34.032505638888885 108.76779925 514.638 34.03267641666667 108.76781155555555 514.464 34.03394725 108.76789833333333 514.635 ''' def API_data0123_to_data123(data0123): data123 = [] for data_i in data0123: data_0 = float (data_i[ 1 ]) data_1 = float (data_i[ 2 ]) data_2 = float (data_i[ 3 ]) data_ii = [data_0,data_1,data_2] data123.append(data_ii) return data123 ''' # 将gnss列表集中转换过去enu 输入: 纬度 经度 高度 列表 34.032505638888885 108.76779925 514.638 34.03267641666667 108.76781155555555 514.464 34.03394725 108.76789833333333 514.635 ''' def API_gnss3_to_enu3_List(gnss0Lat1Lon2H_List): # 4 将gps转滑到enu坐标系 # 4-1 第一帧为参考点 lat0 = float (gnss0Lat1Lon2H_List[ 0 ][ 0 ]) lon0 = float (gnss0Lat1Lon2H_List[ 0 ][ 1 ]) alt0 = float (gnss0Lat1Lon2H_List[ 0 ][ 2 ]) gnss_ref = [lat0,lon0,alt0] if use_cgcs2000Towgs84:gnss_ref = Api_cgcs2000Towgs84(gnss_ref) print ( "参考GNSS位置" ,gnss_ref) ENU_List = [] for gps_i in gnss0Lat1Lon2H_List: lat = float (gps_i[ 0 ]) lon = float (gps_i[ 1 ]) alt = float (gps_i[ 2 ]) gnss_in = [lat,lon,alt] if use_cgcs2000Towgs84:gnss_in = Api_cgcs2000Towgs84(gnss_in) # 4-2 转化坐标系 e, n, u = API_gnss_to_enu(gnss_in,gnss_ref) # e=round(e, 3) # n=round(n, 3) # u=round(u, 3) ENU_List.append([e,n,u]) #print("gnss-enu 单位m",name_,"输入经纬度",lat,lon,alt,"转化后的enu",e, n, u ) return ENU_List # 测试 # Gnss_list_Read = API_read2txt(GPS_txt_name) # 将txt数据去掉第一列 # Gnss0Lat1Lon2H=API_data0123_to_data123(Gnss_list_Read) # ENU_List=API_gnss_to_enu_List(Gnss0Lat1Lon2H) # 4-2 将一个enu在给定gnss参考原点下转换到gnss ''' 功能: # enu直接转化到gnss坐标系 相对于指定GPS_ref为原点(一般都是第一帧)的enu坐标系 输入: from_enu 等待转换的GPS 坐标 lat, lon, h gnss_ref 参考原点GPS 坐标 lat_ref, lon_ref, h_ref 输出: gnss坐标 lat, lon, h ''' def API_enu_to_gnss(from_enu,gnss_ref): e = from_enu[ 0 ] n = from_enu[ 1 ] u = from_enu[ 2 ] lat0 = gnss_ref[ 0 ] lon0 = gnss_ref[ 1 ] alt0 = gnss_ref[ 2 ] # enu转换到ecef 在指定gnss_ref参考点下 x, y, z = enu_to_ecef(e,n,u,lat0, lon0, alt0) # 从ecef转换到gnss gnss_ = ecef_to_gnss(x,y,z) return gnss_ ''' # 将enu列表集中转换过去gnss 输入: 参数1 enu_list_Read e n u 列表 0 0 0 1 0 0 1 1 0 参数2 gnss_ref 参考gnss点 输出 gps 位置 ''' def API_enu3_to_gnss3_list(enu_list_Read,gnss_ref): #gnss_ref=[lat0,lon0,alt0] print ( "参考GNSS位置" ,gnss_ref) GNSS_List = [] for enu_i in enu_list_Read: name_ = enu_i[ 0 ] e = float (enu_i[ 1 ]) n = float (enu_i[ 2 ]) u = float (enu_i[ 3 ]) from_enu_ = [e,n,u] gnss_out = API_enu_to_gnss(from_enu_,gnss_ref) GNSS_List.append([gnss_out[ 0 ],gnss_out[ 1 ],gnss_out[ 2 ]]) return GNSS_List #5-1 多个txt数据 gnss转化到enu # 第一帧为参考帧 def API_gnss4_to_enu4_List(Gnss_list_Read): #GPS_txt_name="d1_100mRTKColmap.txt" # 3读取txt #Gnss_list_Read = API_read2txt(GPS_txt_name) # 4 将gps转滑到enu坐标系 # 4-1 第一帧为参考点 lat0 = float (Gnss_list_Read[ 0 ][ 1 ]) lon0 = float (Gnss_list_Read[ 0 ][ 2 ]) alt0 = float (Gnss_list_Read[ 0 ][ 3 ]) gnss_ref = [lat0,lon0,alt0] if use_cgcs2000Towgs84:gnss_ref = Api_cgcs2000Towgs84(gnss_ref) print ( "参考GNSS位置" ,gnss_ref) ENU_List = [] for gps_i in Gnss_list_Read: lat = float (gps_i[ 1 ]) lon = float (gps_i[ 2 ]) alt = float (gps_i[ 3 ]) gnss_in = [lat,lon,alt] if use_cgcs2000Towgs84:gnss_in = Api_cgcs2000Towgs84(gnss_in) name_ = gps_i[ 0 ] # 4-2 转化坐标系 e, n, u = API_gnss_to_enu(gnss_in,gnss_ref) # e=round(e, 3) # n=round(n, 3) # u=round(u, 3) ENU_List.append([name_,e,n,u]) #print("gnss-enu 单位m",name_,"输入经纬度",lat,lon,alt,"转化后的enu",e, n, u ) return ENU_List #5-2 多个txt数据 enu转化到gnss # 第一帧为参考帧 def API_enu4_to_gnss4_list(enu_list_Read,gnss_ref): #enu_list_Read = API_read2txt(ENU_txt_name) #gnss_ref=[lat0,lon0,alt0] print ( "参考GNSS位置" ,gnss_ref) GNSS_List = [] for enu_i in enu_list_Read: name_ = enu_i[ 0 ] e = float (enu_i[ 1 ]) n = float (enu_i[ 2 ]) u = float (enu_i[ 3 ]) from_enu_ = [e,n,u] gnss_out = API_enu_to_gnss(from_enu_,gnss_ref) GNSS_List.append([name_,gnss_out[ 0 ],gnss_out[ 1 ],gnss_out[ 2 ]]) return GNSS_List #def waitUse(): #import numpy as np #from scipy.spatial.transform import Rotation as R # 将四元数转换为旋转矩阵 # rotation = R.from_quat([qx, qy, qz, qw]) # rotation_matrix = rotation.as_matrix() # # 将旋转矩阵转换为欧拉角 (Omega, Phi, Kappa) # # 摄影测量中通常使用 ZYX 旋转顺序 # omega, phi, kappa = rotation.as_euler('ZYX', degrees=True) # print("旋转矩阵:\n", rotation_matrix) # print("Omega:", omega, "Phi:", phi, "Kappa:", kappa) #=========================================================== # if __name__ == "__main__": # # 参数 # # 0-1 gps照片路径 # img_path_dir="0测试数据/d1_100mRTKColmap/images/gps_images/" # # 0-2 txt保存的名字 # # 1-1从照片读取gnss数据 # Gnss_list=API_read_directory(img_path_dir) # # 1-2保存gps txt # GPS_txt_name="data/1GNSS_from_img.txt" # API_Save2txt(GPS_txt_name,Gnss_list) # # 3 gps转化到enu 第一帧参考位置 # # 3-1 读取GNSS数据 -名字 lat lon h # enu_list_Read = API_read2txt(GPS_txt_name) # # 3-2 gnss数据转换为enu # ENU_List=API_gnss4_to_enu4_List(enu_list_Read) # # 3-2 保存enu结果 -名字 e n u # ENU_txt_name="data/2ENU_from_GNSS.txt" # API_Save2txt(ENU_txt_name,ENU_List) # # 4 读取enu数据 转化到 gnss # # 4-1 获取gnss参考点 - 名字 纬 经 高 # Gnss_list_Read = API_read2txt(GPS_txt_name) # img_name=Gnss_list_Read[0][0] # lat0=float(Gnss_list_Read[0][1]) # lon0=float(Gnss_list_Read[0][2]) # alt0=float(Gnss_list_Read[0][3]) # gnss_ref=[lat0,lon0,alt0] # if use_cgcs2000Towgs84:gnss_ref=Api_cgcs2000Towgs84(gnss_ref) # print("参考GNSS位置",gnss_ref) # # 4-2 获取enu数据集 -名字 e n u # enu_list_Read=API_read2txt(ENU_txt_name) # # 4-3 ENU数据转化为gnss数据 # GNSS_list_from_enu=API_enu4_to_gnss4_list(enu_list_Read,gnss_ref) # # 4-2 保存gnss结果 名字 纬 经 高 # GNSS_From_ENU_txt_name="data/3GNSS_From_ENU.txt" # API_Save2txt(GNSS_From_ENU_txt_name,GNSS_list_from_enu) # # 5 数据转化 为3D-3D计算相似变换准备 # #ENU_List :名字 e n u 转化为: e n u # ENU_List_3=API_data0123_to_data123(ENU_List) # 去掉第一列名字 # GNSS_list_from_enu_3=API_data0123_to_data123(GNSS_list_from_enu) |
数据格式
1GNSS_from_img.txt
1 2 3 4 5 6 7 8 | DJI_0002.JPG 34.032505638888885 108.76779925 514.638 DJI_0005.JPG 34.03267641666667 108.76781155555555 514.464 DJI_0011.JPG 34.03394725 108.76789833333333 514.635 DJI_0015.JPG 34.03487661111111 108.76796561111111 514.642 DJI_0018.JPG 34.03509530555555 108.76797844444444 514.615 DJI_0022.JPG 34.03506447222222 108.76773913888889 514.582 DJI_0025.JPG 34.03463080555555 108.76770336111112 514.66 DJI_0028.JPG 34.03403180555556 108.76765755555556 514.578 |
2ENU_from_GNSS.txt
1 2 3 4 5 6 7 8 9 | DJI_0002.JPG 0.0 0.0 0.0 DJI_0005.JPG 1.136502194718024 18.94471263835052 - 0.1740283354476304 DJI_0011.JPG 9.150887116507509 159.92076256807346 - 0.005018428985010814 DJI_0015.JPG 15.364189902744634 263.01664813277375 - 0.0014604668066482418 DJI_0018.JPG 16.54936288252069 287.2768610609836 - 0.029513647144568722 DJI_0022.JPG - 5.551516671578071 283.8564433571913 - 0.062340937273717145 DJI_0025.JPG - 8.855791726698286 235.74893956148208 0.01762175801103183 DJI_0028.JPG - 13.086242906526223 169.3006810553214 - 0.06226821051640741 DJI_0031.JPG - 17.473255978463847 97.30275378560809 - 0.09176870888806832 |
3GNSS_From_ENU.txt
1 2 3 4 5 6 7 8 9 10 11 12 | DJI_0002.JPG 34.03250563926396 108.7677992500047 514.6380141189607 DJI_0005.JPG 34.03267641704175 108.76781155556024 514.4640141184373 DJI_0011.JPG 34.03394725037507 108.76789833333802 514.635014120011 DJI_0015.JPG 34.03487661148619 108.76796561111581 514.6420141205874 DJI_0018.JPG 34.03509530593064 108.76797844444913 514.6150141188659 DJI_0022.JPG 34.035064472597305 108.76773913889359 514.58201412093 DJI_0025.JPG 34.03463080593064 108.76770336111582 514.6600141209601 DJI_0028.JPG 34.03403180593064 108.76765755556025 514.5780141181838 DJI_0031.JPG 34.033382778152856 108.76761005556025 514.5470141202469 DJI_0035.JPG 34.032533167041734 108.7675511111158 514.6610141190716 DJI_0041.JPG 34.03248758370841 108.7671833611158 514.8310141174146 DJI_0042.JPG 34.03248605593062 108.76717719444913 514.781014119351 |
分类:
1_1_0SLAM工具集合
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