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"cells": [
{
"cell_type": "markdown",
"id": "7d7011e4",
"metadata": {},
"source": [
"## load gt and translate"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "878f605d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"=== 데이터 처리 시작 ===\n",
"\n",
"--- [카테고리: 100\n",
"100_19\n",
"<class 'numpy.ndarray'>\n",
"[ 27.68288937 -86.93143622 -391.88928707] [[-3.44080897e-03 -8.47121477e-01 -5.31388104e-01 4.50000000e+01]\n",
" [ 3.94428801e-03 -5.31398594e-01 8.47112715e-01 -5.40000000e+01]\n",
" [-9.99986291e-01 8.18805187e-04 5.16973250e-03 -3.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_10\n",
"<class 'numpy.ndarray'>\n",
"[ 12.38863746 -57.68256936 -381.29907027] [[-2.60428756e-01 7.87984859e-03 9.65460896e-01 -7.90000000e+01]\n",
" [-9.65479553e-01 -7.41084246e-03 -2.60373324e-01 3.30000000e+01]\n",
" [ 5.10317646e-03 -9.99941468e-01 9.53782909e-03 -3.10000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_1\n",
"<class 'numpy.ndarray'>\n",
"[ 26.85118051 -62.92767834 -370.86569791] [[-9.29776490e-01 1.92658454e-02 3.67620081e-01 -2.75000000e+01]\n",
" [-3.68124545e-01 -4.86602075e-02 -9.28502262e-01 9.00000000e+01]\n",
" [ 8.74227766e-08 -9.98629570e-01 5.23353480e-02 -4.05000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_4\n",
"<class 'numpy.ndarray'>\n",
"[ 23.32426356 -56.67697439 -363.38983436] [[-7.48883605e-01 -5.79744531e-03 -6.62676156e-01 5.50000000e+01]\n",
" [ 6.62134409e-01 -4.79060449e-02 -7.47852266e-01 7.35000000e+01]\n",
" [-2.74105631e-02 -9.98835027e-01 3.97147425e-02 -3.35000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_6\n",
"<class 'numpy.ndarray'>\n",
"[ 26.10227223 -53.11903372 -363.07898045] [[ 1.56853646e-02 -5.31497970e-02 -9.98463333e-01 8.15000000e+01]\n",
" [ 9.98506367e-01 -5.14356159e-02 1.84240397e-02 9.50000000e+00]\n",
" [-5.23358099e-02 -9.97260988e-01 5.22636250e-02 -3.20000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_5\n",
"<class 'numpy.ndarray'>\n",
"[ 12.5959238 -55.35778259 -362.56857363] [[-3.94979000e-01 6.35002041e-03 -9.18668211e-01 7.70000000e+01]\n",
" [ 9.18109953e-01 -3.28056365e-02 -3.94965738e-01 4.20000000e+01]\n",
" [-3.26455347e-02 -9.99441564e-01 7.12752016e-03 -2.70000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_17\n",
"<class 'numpy.ndarray'>\n",
"[ 20.21651818 -75.53526183 -382.48702531] [[ 9.93691802e-01 5.49165793e-02 -9.77794528e-02 8.50000000e+00]\n",
" [ 5.20794094e-02 -9.98151124e-01 -3.13374996e-02 2.80000000e+01]\n",
" [-9.93196219e-02 2.60475185e-02 -9.94714618e-01 5.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_15\n",
"<class 'numpy.ndarray'>\n",
"[ 33.50768481 -84.85182553 -345.91473838] [[ -0.31344265 -0.83292198 -0.45606431 41.5 ]\n",
" [ 0.4717705 -0.55339044 0.68643403 -45. ]\n",
" [ -0.82412761 0. 0.56640416 -80. ]\n",
" [ 0. 0. 0. 1. ]]\n",
"100_12\n",
"<class 'numpy.ndarray'>\n",
"[ 31.24532669 -86.75121609 -353.34212932] [[ 1.42007515e-01 -8.66025984e-01 4.79408890e-01 -3.65000000e+01]\n",
" [-2.45964885e-01 -4.99999017e-01 -8.30362737e-01 8.25000000e+01]\n",
" [ 9.58819687e-01 -4.13823892e-10 -2.84015596e-01 -1.10000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_16\n",
"<class 'numpy.ndarray'>\n",
"[ 30.82814366 -86.79540518 -350.2853077 ] [[ 8.52010548e-02 -8.41476321e-01 -5.33533871e-01 4.60000000e+01]\n",
" [-1.31198451e-01 -5.40293396e-01 8.31185937e-01 -5.30000000e+01]\n",
" [-9.87688065e-01 -8.19094013e-04 -1.56433955e-01 -2.15000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_14\n",
"<class 'numpy.ndarray'>\n",
"[ 11.32912561 -88.72182741 -320.58723623] [[ 5.33357799e-01 8.36590827e-01 1.25080809e-01 -3.00000000e+00]\n",
" [-8.22668970e-01 5.47423184e-01 -1.53439179e-01 2.35000000e+01]\n",
" [-1.96837932e-01 -2.10621152e-02 9.80209768e-01 -1.47500000e+02]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_7\n",
"<class 'numpy.ndarray'>\n",
"[ 21.34627143 -58.16192078 -356.28098385] [[ 5.92012107e-01 4.96898224e-07 -8.05929065e-01 6.80000000e+01]\n",
" [ 8.05929065e-01 -2.56532473e-07 5.92012107e-01 -3.50000000e+01]\n",
" [ 8.74227766e-08 -1.00000000e+00 -5.52335052e-07 -3.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_13\n",
"<class 'numpy.ndarray'>\n",
"[ 59.63980167 -86.6218157 -329.26800774] [[ 8.91008914e-01 -2.37618890e-02 -4.53363568e-01 2.50000000e+01]\n",
" [ 0.00000000e+00 9.98629272e-01 -5.23405969e-02 1.45000000e+01]\n",
" [ 4.53985840e-01 4.66359369e-02 8.89787555e-01 -1.39000000e+02]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_9\n",
"<class 'numpy.ndarray'>\n",
"[ 20.4804379 -64.24306701 -340.3899203 ] [[ 6.69129610e-01 -3.51968282e-07 7.43145764e-01 -6.10000000e+01]\n",
" [-7.43145764e-01 -4.34551595e-07 6.69129610e-01 -4.45000000e+01]\n",
" [ 8.74227766e-08 -1.00000000e+00 -5.52335052e-07 -3.95000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_18\n",
"<class 'numpy.ndarray'>\n",
"[ 29.51497531 -84.28438873 -386.30095596] [[-0.8943522 -0.11493713 -0.43234661 44. ]\n",
" [-0.10348006 0.9933728 -0.0500242 13.5 ]\n",
" [ 0.435231 0. -0.9003188 34.5 ]\n",
" [ 0. 0. 0. 1. ]]\n",
"100_2\n",
"<class 'numpy.ndarray'>\n",
"[ 26.83223131 -63.00083316 -370.87430258] [[-9.49425459e-01 6.57540886e-03 3.13923627e-01 -2.30000000e+01]\n",
" [-3.13992471e-01 -1.98824760e-02 -9.49217260e-01 9.30000000e+01]\n",
" [ 8.74227766e-08 -9.99780715e-01 2.09415592e-02 -4.10000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_11\n",
"<class 'numpy.ndarray'>\n",
"[ 26.90841816 -62.12812932 -380.46406556] [[-1.00000000e+00 -8.73029720e-08 4.57530147e-09 0.00000000e+00]\n",
" [ 0.00000000e+00 -5.23353480e-02 -9.98629570e-01 9.60000000e+01]\n",
" [ 8.74227766e-08 -9.98629570e-01 5.23353480e-02 -4.30000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_20\n",
"<class 'numpy.ndarray'>\n",
"[ 27.88475307 -86.96061947 -391.9093064 ] [[ 9.97695565e-07 -8.38671207e-01 -5.44638038e-01 4.60000000e+01]\n",
" [-1.53632050e-06 -5.44638038e-01 8.38671207e-01 -5.35000000e+01]\n",
" [-1.00000000e+00 0.00000000e+00 -1.83185068e-06 -3.15000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_3\n",
"<class 'numpy.ndarray'>\n",
"[ 17.79732449 -62.35233208 -366.93717212] [[-1.00000000e+00 -8.73029720e-08 4.57530147e-09 1.00000000e+00]\n",
" [ 0.00000000e+00 -5.23353480e-02 -9.98629570e-01 9.65000000e+01]\n",
" [ 8.74227766e-08 -9.98629570e-01 5.23353480e-02 -4.10000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"100_8\n",
"<class 'numpy.ndarray'>\n",
"[ 38.36481646 -71.7701904 -354.06466243] [[ 9.87688005e-01 -8.18929984e-04 -1.56434417e-01 1.50000000e+01]\n",
" [ 1.56436563e-01 5.17100841e-03 9.87674475e-01 -7.20000000e+01]\n",
" [ 8.74227766e-08 -9.99986291e-01 5.23545360e-03 -4.80000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"\n",
"--- [카테고리: 75\n",
"75_6\n",
"<class 'numpy.ndarray'>\n",
"[ 25.47393573 -61.16251869 -346.08127045] [[ 7.43143857e-01 -7.00662425e-03 -6.69095039e-01 5.55000000e+01]\n",
" [ 6.69131696e-01 7.78175192e-03 7.43103087e-01 -4.95000000e+01]\n",
" [ 8.74227766e-08 -9.99945164e-01 1.04713151e-02 -3.65000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_12\n",
"<class 'numpy.ndarray'>\n",
"[ 77.80305291 -88.11463326 -339.23431286] [[ -0.16102958 -0.96174151 0.22163652 -15. ]\n",
" [ 0.56530029 -0.27395853 -0.77806318 72. ]\n",
" [ 0.80901486 0. 0.58778816 -87. ]\n",
" [ 0. 0. 0. 1. ]]\n",
"75_9\n",
"<class 'numpy.ndarray'>\n",
"[ 36.14424874 -45.98588562 -337.09340609] [[-5.23364507e-02 -5.68631492e-07 9.98629510e-01 -8.15000000e+01]\n",
" [-9.98629510e-01 -2.96487542e-07 -5.23364507e-02 1.70000000e+01]\n",
" [ 3.25841370e-07 -1.00000000e+00 -5.52335052e-07 -1.95000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_4\n",
"<class 'numpy.ndarray'>\n",
"[ 28.29367384 -52.6131613 -335.17429047] [[-5.44638991e-01 -3.51193435e-02 -8.37934971e-01 6.75000000e+01]\n",
" [ 8.38670611e-01 -2.28066631e-02 -5.44161260e-01 5.15000000e+01]\n",
" [ 8.74227766e-08 -9.99122858e-01 4.18749601e-02 -2.80000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_11\n",
"<class 'numpy.ndarray'>\n",
"[ 29.62732738 -56.77829678 -335.64674322] [[-9.99876618e-01 -7.39993062e-04 -1.56898778e-02 5.00000000e+00]\n",
" [ 1.57073177e-02 -4.70999852e-02 -9.98766661e-01 9.55000000e+01]\n",
" [ 8.74227766e-08 -9.98889923e-01 4.71058004e-02 -3.60000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_7\n",
"<class 'numpy.ndarray'>\n",
"[ 29.51817746 -73.18091802 -346.48799717] [[ 9.99876618e-01 -1.57069974e-02 2.28808744e-06 1.50000000e+00]\n",
" [-2.29647958e-06 -5.16259831e-07 1.00000000e+00 -7.50000000e+01]\n",
" [-1.57069974e-02 -9.99876618e-01 -5.52266897e-07 -4.80000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_14\n",
"<class 'numpy.ndarray'>\n",
"[ 10.1322433 -85.76779408 -327.42432431] [[-4.33009684e-01 -8.77923250e-01 -2.04336330e-01 1.35000000e+01]\n",
" [ 7.49996722e-01 -4.76651311e-01 4.58593965e-01 -1.35000000e+01]\n",
" [-5.00007510e-01 4.53240424e-02 8.64834249e-01 -1.15500000e+02]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_8\n",
"<class 'numpy.ndarray'>\n",
"[ 26.63627824 -53.98035544 -330.35852582] [[ 7.07105756e-01 3.70067917e-02 7.06138730e-01 -5.80000000e+01]\n",
" [-7.07107782e-01 3.70065644e-02 7.06136763e-01 -4.70000000e+01]\n",
" [ 8.74227766e-08 -9.98629570e-01 5.23353480e-02 -3.15000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_16\n",
"<class 'numpy.ndarray'>\n",
"[ 4.83449077 -87.73546903 -364.27615353] [[-5.13123758e-02 -8.95571470e-01 -4.41948861e-01 3.95000000e+01]\n",
" [ 9.10650045e-02 -4.44884062e-01 8.90946329e-01 -6.05000000e+01]\n",
" [-9.94522095e-01 5.47049567e-03 1.04383275e-01 -3.70000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_17\n",
"<class 'numpy.ndarray'>\n",
"[ -7.67907374 -86.0641732 -369.20247549] [[ -0.29844257 0.89100653 0.34211028 -33. ]\n",
" [ 0.58572644 0.45399052 -0.67142916 67. ]\n",
" [ -0.75356257 0. -0.65737617 13. ]\n",
" [ 0. 0. 0. 1. ]]\n",
"75_2\n",
"<class 'numpy.ndarray'>\n",
"[ 61.57121736 -49.23862344 -341.37979664] [[-4.99314755e-01 5.58332866e-03 8.66402686e-01 -6.95000000e+01]\n",
" [-8.64838541e-01 -6.36153370e-02 -4.98003364e-01 4.95000000e+01]\n",
" [ 5.23359850e-02 -9.97958899e-01 3.65927555e-02 -2.60000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_3\n",
"<class 'numpy.ndarray'>\n",
"[ 44.23895467 -56.75448584 -325.57212978] [[-9.87688363e-01 7.36888452e-03 1.56260818e-01 -1.05000000e+01]\n",
" [-1.56434476e-01 -4.65258621e-02 -9.86591935e-01 9.60000000e+01]\n",
" [ 8.74227766e-08 -9.98889923e-01 4.71058004e-02 -3.75000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_1\n",
"<class 'numpy.ndarray'>\n",
"[ 61.56717855 -49.21549994 -341.35839738] [[-4.53368336e-01 2.29036547e-02 8.91028941e-01 -7.20000000e+01]\n",
" [-8.89785409e-01 -7.03275502e-02 -4.50927883e-01 4.45000000e+01]\n",
" [ 5.23359850e-02 -9.97260988e-01 5.22636212e-02 -2.75000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_21\n",
"<class 'numpy.ndarray'>\n",
"[ 81.0835934 -87.56710011 -344.99450452] [[ 3.96303624e-01 -6.81974113e-01 -6.14698887e-01 4.60000000e+01]\n",
" [ 3.61055166e-01 7.31339276e-01 -5.78603566e-01 5.70000000e+01]\n",
" [ 8.44146073e-01 7.36248400e-03 5.36062658e-01 -8.80000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_15\n",
"<class 'numpy.ndarray'>\n",
"[ 31.48993665 -84.54804326 -340.47380349] [[-2.66847461e-01 -9.13924754e-01 -3.05833250e-01 2.70000000e+01]\n",
" [ 5.23719072e-01 -4.03910011e-01 7.50050068e-01 -4.25000000e+01]\n",
" [-8.09018433e-01 3.99782509e-02 5.86422145e-01 -7.25000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_20\n",
"<class 'numpy.ndarray'>\n",
"[ 24.55639443 -88.8606151 -373.10931148] [[ 0.27724347 -0.86074269 0.42691699 -33.5 ]\n",
" [ -0.46879447 -0.5090403 -0.7218793 71.5 ]\n",
" [ 0.83867025 0. -0.54463947 22.5 ]\n",
" [ 0. 0. 0. 1. ]]\n",
"75_10\n",
"<class 'numpy.ndarray'>\n",
"[ 48.41003362 -51.46534158 -342.23811088] [[-7.76975513e-01 1.66823063e-02 6.29309773e-01 -5.15000000e+01]\n",
" [-6.29182398e-01 -5.38339429e-02 -7.75391161e-01 7.50000000e+01]\n",
" [ 2.09429134e-02 -9.98410523e-01 5.23238666e-02 -3.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_13\n",
"75_5\n",
"<class 'numpy.ndarray'>\n",
"[ 18.01187147 -53.76846861 -340.13700206] [[ 4.63267155e-02 -2.42990740e-02 -9.98630762e-01 8.20000000e+01]\n",
" [ 9.98924851e-01 -5.92150493e-04 4.63547669e-02 6.00000000e+00]\n",
" [-1.71771762e-03 -9.99704540e-01 2.42455173e-02 -2.85000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_19\n",
"<class 'numpy.ndarray'>\n",
"[ 39.95805372 -83.76133353 -374.33282491] [[-9.49753225e-01 -5.55646084e-02 -3.08028281e-01 3.00000000e+01]\n",
" [-4.97744568e-02 9.98405397e-01 -2.66292337e-02 1.10000000e+01]\n",
" [ 3.09016734e-01 -9.95925907e-03 -9.51004446e-01 4.50000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"75_18\n",
"<class 'numpy.ndarray'>\n",
"[ 32.33949994 -78.34503029 -373.98941981] [[-1.53016374e-01 -9.87688303e-01 3.25245820e-02 7.00000000e+00]\n",
" [-9.66104984e-01 1.56434834e-01 2.05351636e-01 -9.50000000e+00]\n",
" [-2.07911372e-01 0.00000000e+00 -9.78147686e-01 5.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"\n",
"--- [카테고리: 50\n",
"50_18\n",
"<class 'numpy.ndarray'>\n",
"[ 37.6490856 -74.61372578 -381.71563518] [[ 0.7006287 -0.58778656 -0.40450755 42.5 ]\n",
" [-0.50903827 -0.80901605 0.29389292 -1. ]\n",
" [-0.49999943 0. -0.86602575 30. ]\n",
" [ 0. 0. 0. 1. ]]\n",
"50_8\n",
"<class 'numpy.ndarray'>\n",
"[ 45.25869642 -31.75810295 -340.34899081] [[-2.23250553e-01 5.61106019e-02 9.73144770e-01 -7.10000000e+01]\n",
" [-9.74761069e-01 -1.28511591e-02 -2.22880363e-01 3.15000000e+01]\n",
" [ 8.74227766e-08 -9.98341858e-01 5.75634576e-02 -1.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_13\n",
"<class 'numpy.ndarray'>\n",
"[ 88.33799044 -89.27276883 -324.15194501] [[-9.65258181e-02 9.87688482e-01 1.23102739e-01 -3.00000000e+00]\n",
" [-6.09442890e-01 -1.56433746e-01 7.77243733e-01 -1.95000000e+01]\n",
" [ 7.86932111e-01 0.00000000e+00 6.17039621e-01 -1.17000000e+02]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_15\n",
"<class 'numpy.ndarray'>\n",
"[ 38.07790641 -84.47923114 -353.92594238] [[-7.96265453e-02 -8.62667978e-01 4.99463290e-01 -3.75000000e+01]\n",
" [ 1.67739302e-01 -5.05505145e-01 -8.46361697e-01 8.05000000e+01]\n",
" [ 9.82610345e-01 1.63867678e-02 1.84954956e-01 -3.60000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_7\n",
"<class 'numpy.ndarray'>\n",
"[ 19.2258121 -58.81749421 -329.23658292] [[ 8.94694567e-01 -1.59265324e-02 4.46394473e-01 -4.25000000e+01]\n",
" [-4.45589781e-01 3.79090272e-02 8.94434273e-01 -5.60000000e+01]\n",
" [-3.11676171e-02 -9.99154270e-01 2.68203001e-02 -3.30000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_4\n",
"<class 'numpy.ndarray'>\n",
"[ 34.9035819 -41.77905229 -324.61794059] [[-1.00000000e+00 -8.73461019e-08 3.66078368e-09 1.50000000e+00]\n",
" [ 0.00000000e+00 -4.18744832e-02 -9.99122858e-01 9.20000000e+01]\n",
" [ 8.74227766e-08 -9.99122858e-01 4.18744832e-02 -2.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_5\n",
"<class 'numpy.ndarray'>\n",
"[ 26.45149554 -59.00732366 -342.11193051] [[-3.09017181e-01 -4.97738943e-02 -9.49753106e-01 7.65000000e+01]\n",
" [ 9.51056480e-01 -1.61724389e-02 -3.08593690e-01 3.35000000e+01]\n",
" [ 8.74227766e-08 -9.98629570e-01 5.23353480e-02 -3.90000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_19\n",
"<class 'numpy.ndarray'>\n",
"[ 40.13537403 -85.52798879 -378.05115358] [[ 1.79187074e-01 -8.66021454e-01 -4.66796309e-01 4.15000000e+01]\n",
" [-3.10355484e-01 -5.00006795e-01 8.08500230e-01 -4.70000000e+01]\n",
" [-9.33579922e-01 -5.22160648e-10 -3.58369291e-01 -6.00000000e+00]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_16\n",
"<class 'numpy.ndarray'>\n",
"[ 31.5785426 -85.40193305 -347.10507971] [[ 0.19544786 -0.89100701 0.40976411 -28. ]\n",
" [ -0.38358906 -0.45398954 -0.80420953 79. ]\n",
" [ 0.90258491 0. -0.43051183 10. ]\n",
" [ 0. 0. 0. 1. ]]\n",
"50_20\n",
"<class 'numpy.ndarray'>\n",
"[ 1.7647396 -84.41729645 -385.40808541] [[-6.57805651e-02 -7.77146757e-01 -6.25872016e-01 4.65000000e+01]\n",
" [ 8.12324509e-02 -6.29319370e-01 7.72889674e-01 -4.15000000e+01]\n",
" [-9.94522095e-01 1.52299992e-10 1.04526527e-01 -4.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_14\n",
"<class 'numpy.ndarray'>\n",
"[ 0.59275917 -86.71000009 -337.64247339] [[ 6.21570587e-01 1.96392089e-01 7.58340418e-01 -4.25000000e+01]\n",
" [-9.84471068e-02 9.79972124e-01 -1.73097655e-01 2.20000000e+01]\n",
" [-7.77147472e-01 3.29359882e-02 6.28456056e-01 -9.95000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_12\n",
"<class 'numpy.ndarray'>\n",
"[ 117.17553538 -107.28665103 -412.27994755] [[ -0.45526764 -0.824081 -0.33707839 12. ]\n",
" [ 0.77621156 -0.55281508 0.30313545 -34.5 ]\n",
" [ -0.43615019 -0.12363636 0.89134002 15.5 ]\n",
" [ 0. 0. 0. 1. ]]\n",
"50_11\n",
"<class 'numpy.ndarray'>\n",
"[ 4.54073889 -36.59589834 -323.56611368] [[-4.71070223e-02 5.47603634e-07 -9.98889863e-01 7.90000000e+01]\n",
" [ 9.98889863e-01 1.13344583e-07 -4.71070223e-02 1.25000000e+01]\n",
" [ 8.74227766e-08 -1.00000000e+00 -5.52335052e-07 -1.10000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_9\n",
"<class 'numpy.ndarray'>\n",
"[ 19.32465046 -54.57283732 -332.86498841] [[-1.00000000e+00 -8.73257306e-08 4.11812007e-09 1.00000000e+00]\n",
" [ 0.00000000e+00 -4.71058004e-02 -9.98889923e-01 9.45000000e+01]\n",
" [ 8.74227766e-08 -9.98889923e-01 4.71058004e-02 -3.35000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_6\n",
"<class 'numpy.ndarray'>\n",
"[ 1.3415373 -65.53985766 -343.89651885] [[ 3.04032058e-01 5.52767858e-07 -9.52661812e-01 8.05000000e+01]\n",
" [ 9.52661812e-01 -8.46432187e-08 3.04032058e-01 -1.00000000e+01]\n",
" [ 8.74227766e-08 -1.00000000e+00 -5.52335052e-07 -4.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_17\n",
"<class 'numpy.ndarray'>\n",
"[ 41.52229701 -81.78741541 -372.03098793] [[ 0.37972054 -0.90466535 0.19337246 -10. ]\n",
" [ -0.85286868 -0.42331231 -0.30564973 44.5 ]\n",
" [ 0.35836765 -0.04885983 -0.9323011 45. ]\n",
" [ 0. 0. 0. 1. ]]\n",
"50_1\n",
"<class 'numpy.ndarray'>\n",
"[ 48.46492655 -69.60127275 -319.69185277] [[ 8.34075391e-01 -6.76482990e-02 5.47486961e-01 -5.15000000e+01]\n",
" [-5.41656852e-01 8.76238346e-02 8.36020291e-01 -5.95000000e+01]\n",
" [-1.04528263e-01 -9.93853986e-01 3.64427119e-02 -4.85000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_10\n",
"<class 'numpy.ndarray'>\n",
"[ -3.11142664 -59.88902055 -328.28775107] [[-6.29320383e-01 -4.06722575e-02 -7.76080966e-01 6.60000000e+01]\n",
" [ 7.77145982e-01 -3.29356305e-02 -6.28457963e-01 6.05000000e+01]\n",
" [ 8.74227766e-08 -9.98629570e-01 5.23353480e-02 -3.75000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_3\n",
"<class 'numpy.ndarray'>\n",
"[ 62.53423076 -20.88353644 -330.04214586] [[-6.29320383e-01 -4.84261932e-07 7.77145982e-01 -5.55000000e+01]\n",
" [-7.77145982e-01 2.79655438e-07 -6.29320383e-01 5.90000000e+01]\n",
" [ 8.74227766e-08 -1.00000000e+00 -5.52335052e-07 5.00000000e+00]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"50_2\n",
"<class 'numpy.ndarray'>\n",
"[ 48.88866993 -69.59724289 -319.57045526] [[ 8.95710886e-01 2.32703052e-02 4.44027543e-01 -3.85000000e+01]\n",
" [-4.44636911e-01 4.68773022e-02 8.94483387e-01 -6.50000000e+01]\n",
" [ 8.74227766e-08 -9.98629570e-01 5.23353480e-02 -4.95000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"\n",
"--- [카테고리: 25\n",
"25_6\n",
"<class 'numpy.ndarray'>\n",
"[ 25.82810838 -6.9878033 -403.72262251] [[-7.88405478e-01 4.83430400e-02 6.13253415e-01 -4.20000000e+01]\n",
" [-6.13420010e-01 1.30563779e-02 -7.89648950e-01 6.60000000e+01]\n",
" [-4.61808965e-02 -9.98745441e-01 1.93608664e-02 2.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_19\n",
"<class 'numpy.ndarray'>\n",
"[ 65.76817148 -89.69543279 -430.61570009] [[ 1.89555846e-02 9.84456241e-01 1.74603984e-01 -1.40000000e+01]\n",
" [-2.58121908e-01 1.73533753e-01 -9.50399458e-01 7.55000000e+01]\n",
" [-9.65926349e-01 -2.70537399e-02 2.57399172e-01 -1.55000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_17\n",
"<class 'numpy.ndarray'>\n",
"[ 22.15794766 -94.17964136 -448.0520384 ] [[-2.32060909e-01 8.42611849e-01 4.85955805e-01 -3.25000000e+01]\n",
" [-3.56040359e-01 -5.38504958e-01 7.63706505e-01 -4.50000000e+01]\n",
" [ 9.05197740e-01 4.20655636e-03 4.24969792e-01 4.00000000e+00]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_9\n",
"<class 'numpy.ndarray'>\n",
"[ 21.94665846 -34.40180524 -411.086406 ] [[ 8.86938572e-01 7.36090913e-02 -4.55984265e-01 4.50000000e+01]\n",
" [ 4.57643390e-01 -6.52838405e-03 8.89111876e-01 -5.85000000e+01]\n",
" [ 6.24698736e-02 -9.97265816e-01 -3.94769907e-02 -1.50000000e+00]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_11\n",
"<class 'numpy.ndarray'>\n",
"[ 14.88917501 2.8271436 -430.23861956] [[ 4.39691365e-01 -2.48752702e-02 8.97804379e-01 -6.75000000e+01]\n",
" [-8.98068964e-01 -2.55144555e-02 4.39114034e-01 -2.35000000e+01]\n",
" [ 1.19839106e-02 -9.99364913e-01 -3.35581936e-02 3.10000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_20\n",
"<class 'numpy.ndarray'>\n",
"[ 75.49902536 -90.79572344 -410.52119793] [[-8.15448537e-02 9.51056480e-01 2.98063844e-01 -2.00000000e+01]\n",
" [ 2.50969082e-01 3.09017181e-01 -9.17345583e-01 6.70000000e+01]\n",
" [-9.64554310e-01 -2.35739928e-10 -2.63884515e-01 2.65000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_14\n",
"<class 'numpy.ndarray'>\n",
"[ 69.7930935 -94.23200028 -390.45061813] [[ 2.91593105e-01 8.57757449e-01 -4.23350453e-01 3.30000000e+01]\n",
" [ 4.38117802e-01 -5.13194382e-01 -7.38027275e-01 6.65000000e+01]\n",
" [-8.50309491e-01 2.97262911e-02 -5.25442779e-01 5.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_4\n",
"<class 'numpy.ndarray'>\n",
"[ 30.55755988 -0.71353162 -407.96803344] [[ 6.90245152e-01 -3.58072780e-02 7.22689033e-01 -5.40000000e+01]\n",
" [-7.22376943e-01 2.33640168e-02 6.91104710e-01 -4.00000000e+01]\n",
" [-4.16314974e-02 -9.99085546e-01 -9.73945204e-03 2.75000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_16\n",
"<class 'numpy.ndarray'>\n",
"[ 58.55963505 -93.71161444 -417.38778923] [[ 1.40951931e-01 8.38847995e-01 5.25800884e-01 -3.80000000e+01]\n",
" [ 2.09101275e-01 -5.44346571e-01 8.12381327e-01 -4.95000000e+01]\n",
" [ 9.67682421e-01 -4.56109643e-03 -2.52130896e-01 2.90000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_5\n",
"<class 'numpy.ndarray'>\n",
"[ 34.53011498 -13.30182474 -411.05843229] [[-2.26842333e-02 5.45274513e-03 9.99727786e-01 -7.40000000e+01]\n",
" [-9.99736547e-01 -3.63107515e-03 -2.26646271e-02 1.00000000e+01]\n",
" [ 3.50650237e-03 -9.99978542e-01 5.53367659e-03 1.55000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_2\n",
"<class 'numpy.ndarray'>\n",
"[ 49.02362307 -17.02642286 -420.14247679] [[ 6.76874876e-01 3.85248214e-02 -7.35089302e-01 5.75000000e+01]\n",
" [ 7.36098111e-01 -3.54251638e-02 6.75947189e-01 -4.15000000e+01]\n",
" [ 8.74227766e-08 -9.98629510e-01 -5.23364507e-02 1.20000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_10\n",
"<class 'numpy.ndarray'>\n",
"[ 8.91700337 -46.88344847 -412.80415894] [[ 9.86856818e-01 3.61686666e-03 1.61556527e-01 -8.00000000e+00]\n",
" [-1.61295891e-01 -3.89582254e-02 9.86136854e-01 -7.00000000e+01]\n",
" [ 9.86068137e-03 -9.99234319e-01 -3.78628075e-02 -1.55000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_3\n",
"<class 'numpy.ndarray'>\n",
"[ 34.82892437 -50.73662087 -402.10128476] [[ 9.85264003e-01 1.82937104e-02 -1.70059204e-01 1.85000000e+01]\n",
" [ 1.70880020e-01 -6.22430854e-02 9.83323872e-01 -7.05000000e+01]\n",
" [ 7.40363169e-03 -9.97893333e-01 -6.44519031e-02 -1.95000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_8\n",
"<class 'numpy.ndarray'>\n",
"[ 29.26225048 -6.01445517 -397.04172916] [[-4.91195738e-01 -7.68628204e-03 -8.71015310e-01 6.50000000e+01]\n",
" [ 8.70001376e-01 -5.33626601e-02 -4.90153044e-01 3.65000000e+01]\n",
" [-4.27122414e-02 -9.98545587e-01 3.28985862e-02 2.05000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_13\n",
"<class 'numpy.ndarray'>\n",
"[ 81.12690397 -93.30045453 -410.25034345] [[-5.47061302e-03 8.38813305e-01 -5.44391692e-01 4.20000000e+01]\n",
" [-1.04383267e-01 -5.41904807e-01 -8.33932459e-01 6.55000000e+01]\n",
" [-9.94522095e-01 5.22632636e-02 9.05226246e-02 5.00000000e-01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_7\n",
"<class 'numpy.ndarray'>\n",
"[ 28.43852254 -9.56659492 -397.66124973] [[-9.98629510e-01 -5.83959867e-08 -5.23359589e-02 8.00000000e+00]\n",
" [ 5.23359589e-02 5.56153452e-07 -9.98629510e-01 9.05000000e+01]\n",
" [ 8.74227766e-08 -1.00000000e+00 -5.52335052e-07 1.75000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_12\n",
"<class 'numpy.ndarray'>\n",
"[ 13.72683538 -91.41095803 -356.27025592] [[ 1.69210151e-01 -9.68068361e-01 1.84963837e-01 -1.25000000e+01]\n",
" [ 7.75157630e-01 2.46622428e-01 5.81642509e-01 -1.00000000e+01]\n",
" [-6.08685970e-01 4.49563079e-02 7.92136550e-01 -1.23000000e+02]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_1\n",
"<class 'numpy.ndarray'>\n",
"[ 49.14660212 -17.12709575 -420.12002518] [[ 6.68827116e-01 1.01306168e-02 -7.43348956e-01 5.60000000e+01]\n",
" [ 7.43384778e-01 3.35009623e-04 6.68863952e-01 -4.15000000e+01]\n",
" [ 7.02503324e-03 -9.99948621e-01 -7.30688265e-03 1.15000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"25_15\n",
"<class 'numpy.ndarray'>\n",
"[ 49.98467752 -79.86515627 -381.91842617] [[ 0.62463939 0.77754307 -0.07247364 1. ]\n",
" [ 0.7536121 -0.62452501 -0.20502999 39. ]\n",
" [-0.20468125 0.0734528 -0.97606879 62.5 ]\n",
" [ 0. 0. 0. 1. ]]\n",
"25_18\n",
"<class 'numpy.ndarray'>\n",
"[ 75.32313965 -51.94009834 -426.54199221] [[ 3.90654840e-02 7.15907872e-01 6.97100997e-01 -3.95000000e+01]\n",
" [-9.99230802e-01 2.55956277e-02 2.97106467e-02 1.20000000e+01]\n",
" [ 3.42734787e-03 -6.97725415e-01 7.16357052e-01 -7.25000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"\n",
"--- [카테고리: 0\n",
"0_12\n",
"<class 'numpy.ndarray'>\n",
"[ 33.12100355 -89.304873 -430.80067399] [[-2.69314437e-03 -8.37908268e-01 -5.45804441e-01 2.95000000e+01]\n",
" [-4.38461453e-02 5.45380473e-01 -8.37041020e-01 5.40000000e+01]\n",
" [ 9.99034643e-01 2.16771476e-02 -3.82078327e-02 1.70000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_17\n",
"<class 'numpy.ndarray'>\n",
"[ 63.18971135 -104.65871516 -417.48397296] [[ -0.17057435 -0.97205442 -0.16129027 5.5 ]\n",
" [ 0.87323803 -0.22495802 0.43226054 -26. ]\n",
" [ -0.45646432 -0.06711224 0.88720697 -50.5 ]\n",
" [ 0. 0. 0. 1. ]]\n",
"0_16\n",
"<class 'numpy.ndarray'>\n",
"[ 90.60255714 -95.06914904 -436.07156899] [[-9.69967321e-02 -8.91160131e-01 -4.43198889e-01 2.60000000e+01]\n",
" [ 1.90232754e-01 -4.53688890e-01 8.70619237e-01 -4.65000000e+01]\n",
" [-9.76935565e-01 1.36282266e-04 2.13534176e-01 1.30000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_15\n",
"<class 'numpy.ndarray'>\n",
"[ 85.73871163 -97.97647058 -345.40642729] [[ 2.42001772e-01 -8.76848459e-01 -4.15417761e-01 2.60000000e+01]\n",
" [-5.20891607e-01 -4.78624433e-01 7.06817210e-01 -4.35000000e+01]\n",
" [-8.18600655e-01 4.53366153e-02 -5.72570980e-01 9.15000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_2\n",
"<class 'numpy.ndarray'>\n",
"[ 59.93541219 31.87719523 -419.48278269] [[-2.95658797e-01 -9.69152246e-03 -9.55244422e-01 6.40000000e+01]\n",
" [ 9.53975081e-01 -5.55142686e-02 -2.94702709e-01 1.90000000e+01]\n",
" [-5.01735769e-02 -9.98410881e-01 2.56587528e-02 5.75000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_5\n",
"<class 'numpy.ndarray'>\n",
"[ 65.88325717 4.34117716 -403.47988102] [[-9.96179819e-01 8.15538317e-02 3.12203020e-02 -5.00000000e-01]\n",
" [ 8.06401521e-02 9.96307075e-01 -2.94861421e-02 3.50000000e+00]\n",
" [-3.35097164e-02 -2.68558916e-02 -9.99077499e-01 1.13000000e+02]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_14\n",
"<class 'numpy.ndarray'>\n",
"[ 44.31647502 -81.2624644 -361.55233039] [[-3.84653121e-01 -8.88352692e-01 -2.50741839e-01 7.00000000e+00]\n",
" [-9.12658155e-01 4.06685114e-01 -4.07710671e-02 -8.50000000e+00]\n",
" [ 1.38192058e-01 2.13158861e-01 -9.67195034e-01 8.65000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_9\n",
"<class 'numpy.ndarray'>\n",
"[ 60.65603049 11.01128271 -412.31618085] [[-9.51056480e-01 -1.29405009e-02 3.08745980e-01 -2.10000000e+01]\n",
" [-3.09017062e-01 3.98264751e-02 -9.50222254e-01 9.20000000e+01]\n",
" [ 8.74227766e-08 -9.99122798e-01 -4.18760628e-02 4.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_4\n",
"<class 'numpy.ndarray'>\n",
"[ 71.2152848 31.54413173 -418.99812114] [[ 8.23373139e-01 3.39775719e-02 -5.66482306e-01 3.95000000e+01]\n",
" [ 5.66920936e-01 -9.43426564e-02 8.18352044e-01 -5.15000000e+01]\n",
" [-2.56378297e-02 -9.94959772e-01 -9.69418138e-02 6.55000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_18\n",
"<class 'numpy.ndarray'>\n",
"[ 77.77541212 32.49285059 -498.58374177] [[ 7.39454105e-02 -6.21830702e-01 -7.79652894e-01 4.70000000e+01]\n",
" [ 9.95340884e-01 -2.48792651e-03 9.63864326e-02 -5.00000000e+00]\n",
" [-6.18757606e-02 -7.83147752e-01 6.18749559e-01 3.50000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_8\n",
"<class 'numpy.ndarray'>\n",
"[ 51.21758882 33.51005377 -433.44084132] [[-5.67888319e-01 -5.56102134e-02 8.21224928e-01 -5.35000000e+01]\n",
" [-8.22894096e-01 1.57407653e-02 -5.67976713e-01 3.60000000e+01]\n",
" [ 1.86585970e-02 -9.98328447e-01 -5.47003113e-02 6.60000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_7\n",
"<class 'numpy.ndarray'>\n",
"[ 58.3931357 38.96036583 -429.46788448] [[-1.04724206e-02 5.23324758e-02 9.98574793e-01 -5.25000000e+01]\n",
" [-9.99945164e-01 -5.48165059e-04 -1.04580643e-02 1.00000000e+00]\n",
" [ 8.74227766e-08 -9.98629570e-01 5.23353480e-02 6.40000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_11\n",
"<class 'numpy.ndarray'>\n",
"[ 64.95978167 37.09166687 -432.4850532 ] [[-1.50399938e-01 6.99209347e-02 -9.86149549e-01 6.50000000e+01]\n",
" [ 9.86464441e-01 -5.53002842e-02 -1.54368922e-01 8.50000000e+00]\n",
" [-6.53279722e-02 -9.96018529e-01 -6.06573597e-02 6.90000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_13\n",
"<class 'numpy.ndarray'>\n",
"[ -1.6930905 -88.70703015 -362.66812799] [[ -0.34549183 -0.809017 -0.475528 29.5 ]\n",
" [ -0.47552875 0.58778524 -0.65450817 46.5 ]\n",
" [ 0.80901659 0. -0.58778584 100. ]\n",
" [ 0. 0. 0. 1. ]]\n",
"0_10\n",
"<class 'numpy.ndarray'>\n",
"[ 59.88399633 31.37328809 -431.20527244] [[-8.50240290e-01 -7.80269504e-02 -5.20579755e-01 3.40000000e+01]\n",
" [ 5.24040997e-01 -3.20484303e-02 -8.51089835e-01 6.75000000e+01]\n",
" [ 4.97241803e-02 -9.96436000e-01 6.81381896e-02 5.30000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_19\n",
"<class 'numpy.ndarray'>\n",
"[ -28.88535617 -81.14775822 -488.30475985] [[ 3.09901804e-01 -7.05368996e-01 -6.37507200e-01 3.60000000e+01]\n",
" [ 2.82905936e-01 7.08558500e-01 -6.46458864e-01 3.70000000e+01]\n",
" [ 9.07703221e-01 1.99842155e-02 4.19136643e-01 4.15000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_1\n",
"<class 'numpy.ndarray'>\n",
"[ 60.36258594 36.23198051 -421.58748101] [[-2.81364411e-01 -5.52946888e-02 -9.58006561e-01 6.25000000e+01]\n",
" [ 9.59449232e-01 1.54352782e-03 -2.81877220e-01 1.85000000e+01]\n",
" [ 1.70650221e-02 -9.98468876e-01 5.26181534e-02 6.15000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_6\n",
"<class 'numpy.ndarray'>\n",
"[ 61.13838929 38.58341229 -422.8021234 ] [[ 7.30503440e-01 -3.40639576e-02 6.82058930e-01 -4.40000000e+01]\n",
" [-6.82892859e-01 -2.95656901e-02 7.29920030e-01 -4.20000000e+01]\n",
" [-4.69842041e-03 -9.98982251e-01 -4.48598713e-02 7.05000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_20\n",
"<class 'numpy.ndarray'>\n",
"[ 8.04134105e-02 -8.63287174e+01 -4.46489399e+02] [[-9.26770456e-03 -6.92285478e-01 -7.21564233e-01 4.30000000e+01]\n",
" [-5.15075736e-02 7.20967829e-01 -6.91051662e-01 4.95000000e+01]\n",
" [ 9.98629630e-01 3.07615604e-02 -4.23396602e-02 2.95000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n",
"0_3\n",
"<class 'numpy.ndarray'>\n",
"[ 72.09319748 39.45522678 -427.66834818] [[ 4.30095732e-01 5.04564121e-02 -9.01372194e-01 5.95000000e+01]\n",
" [ 9.02783275e-01 -2.38277316e-02 4.29435253e-01 -2.45000000e+01]\n",
" [ 1.90107035e-04 -9.98441994e-01 -5.57994097e-02 7.00000000e+01]\n",
" [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]\n"
]
}
],
"source": [
"import json\n",
"import numpy as np\n",
"\n",
"name = \"bottle2\"\n",
"folder = \"./dataset\"\n",
"json_path = \"ply_files.json\"\n",
"\n",
"try:\n",
" with open(json_path, \"r\", encoding=\"utf-8\") as f:\n",
" categorized_files = json.load(f)\n",
"except FileNotFoundError:\n",
" print(f\"오류: '{json_path}' 파일을 찾을 수 없습니다. 먼저 파일 분류 코드를 실행해 주세요.\")\n",
" exit() # 파일이 없으면 프로그램 종료\n",
"\n",
"# 3. 모든 카테고리와 파일을 순회하는 반복문\n",
"print(\"=== 데이터 처리 시작 ===\")\n",
"categories = [\"100\", \"75\", \"50\", \"25\", \"0\"]\n",
"\n",
"# resolutions 딕셔너리를 기준으로 외부 루프를 실행합니다.\n",
"for category in categories:\n",
" \n",
" print(f\"\\n--- [카테고리: {category}\")\n",
" \n",
" # JSON에서 현재 카테고리에 해당하는 파일 리스트를 가져옵니다.\n",
" # .get(category, [])를 사용하면 JSON에 해당 카테고리가 없어도 오류 없이 빈 리스트를 반환합니다.\n",
" filenames_in_category = categorized_files.get(category, [])\n",
" \n",
" if not filenames_in_category:\n",
" print(\"처리할 파일이 없습니다.\")\n",
" continue # 파일이 없으면 다음 카테고리로 넘어감\n",
"\n",
" # 내부 루프에서 해당 카테고리의 모든 파일을 하나씩 처리합니다.\n",
" for filename in filenames_in_category:\n",
" gt_path =f\"./gt/noisy_filtered_{filename}.json\"\n",
" print(filename)\n",
" try:\n",
" with open(gt_path, \"r\", encoding='utf-8') as f:\n",
" gt_processed = json.load(f)\n",
" gt = np.array(gt_processed[f\"noisy_filtered_{filename}\"][\"matrix_world\"])\n",
"\n",
" print(type(gt))\n",
" ## get translted \n",
" center_path = f\"./centroid/{filename}.txt\"\n",
" translated = np.loadtxt(center_path) \n",
" print(translated, gt)\n",
" ## generate translate T\n",
" tran_T = np.eye(4)\n",
" tran_T[0:3,3] = translated\n",
" \n",
"\n",
" final_T = gt @ tran_T\n",
" real_final_T = np.linalg.inv(final_T)\n",
"\n",
" gt_list = real_final_T.tolist()\n",
" gt_processed[f\"noisy_filtered_{filename}\"][\"matrix_world\"] = gt_list\n",
"\n",
" with open(f'./gt_raw/noisy_filtered_{filename}.json', 'w', encoding='utf-8') as f:\n",
" json.dump(gt_processed, f, ensure_ascii=False, indent=4)\n",
"\n",
"\n",
" except FileNotFoundError:\n",
" continue"
]
},
{
"cell_type": "markdown",
"id": "a0277328",
"metadata": {},
"source": [
"## verify"
]
},
{
"cell_type": "markdown",
"id": "b69bef25",
"metadata": {},
"source": []
},
{
"cell_type": "code",
"execution_count": 9,
"id": "463b3159",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0_6\n",
"\u001b[1;33m[Open3D WARNING] Read PLY failed: unable to read file: ./gt_filtered.ply\u001b[0;m\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"RPly: Unexpected end of file\n",
"RPly: Error reading 'view_px' of 'camera' number 0\n"
]
}
],
"source": [
"import json\n",
"import numpy as np\n",
"import open3d as o3d\n",
"\n",
"\n",
"def get_T(file_path):\n",
" with open(file_path, 'r') as f:\n",
" T_matrix = np.loadtxt(file_path)\n",
" print(T_matrix)\n",
" return T_matrix\n",
" \n",
"filenames = []\n",
"with open(\"filename.txt\", \"r\") as f:\n",
" for line in f:\n",
" filenames.append(line.strip())\n",
"\n",
"\n",
"filename = filenames[0]\n",
"print(filename)\n",
"\n",
"with open(f\"./gt_raw/noisy_filtered_{filename}.json\", 'r') as f:\n",
" loaded_data = json.load(f)\n",
"\n",
"\n",
"\n",
"noisy_data = loaded_data[f'noisy_filtered_{filename}']\n",
"T_matrix = noisy_data['matrix_world']\n",
"\n",
"\n",
"##Translated\n",
"\n",
"gt_path = \"./gt_filtered.ply\"\n",
"noisy_path = f\"./dataset/{filename}.ply\"\n",
"translated_path = f\"./result3/result_{filename}.ply\"\n",
"\n",
"\n",
"\n",
"gt_pcd = o3d.io.read_point_cloud(gt_path)\n",
"gt_pcd.paint_uniform_color([0,0,1])\n",
"noisy_pcd = o3d.io.read_point_cloud(noisy_path)\n",
"noisy_pcd.paint_uniform_color([1,0,0])\n",
"\n",
"translated_noisy_pcd = o3d.io.read_point_cloud(translated_path)\n",
"translated_noisy_pcd.paint_uniform_color([0,1,0])\n",
"\n",
"\n",
"gt = np.array(T_matrix)\n",
"\n",
"## move and check gt and noisy\n",
"\n",
"o3d.visualization.draw_geometries([gt_pcd, noisy_pcd, translated_noisy_pcd])\n",
"# noisy_pcd.transform(tran_T)\n",
"gt_pcd.transform(gt)\n",
"\n",
"o3d.visualization.draw_geometries([noisy_pcd, translated_noisy_pcd])\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|