sk
95c662018d
increase training crop dtom 769 t o1281 for all models + 7 edges for Karusell dataset_v2_88
424 lines
13 KiB
Python
424 lines
13 KiB
Python
import os
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import numpy as np
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try:
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import matplotlib.cm as mplcm
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from matplotlib.animation import FuncAnimation
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from mpl_toolkits.mplot3d import Axes3D
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except ImportError:
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pass
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import openpifpaf
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CAR_KEYPOINTS_24 = list(range(1, 89))
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CAR_SKELETON_24 = [[ 1, 2],
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[ 2, 3],
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[ 3, 4],
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[ 4, 5],
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[ 5, 6],
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[ 6, 7],
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[ 7, 8],
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[ 8, 9],
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[ 9, 10],
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[10, 11],
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[11, 12],
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[12, 13],
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[13, 14],
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[14, 15],
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[15, 16],
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[16, 17],
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[17, 18],
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[18, 19],
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[19, 20],
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[20, 21],
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[21, 22],
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[22, 23],
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[25, 26],
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[23, 24],
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[24, 25],
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[26, 27],
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[27, 28],
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[28, 29],
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[29, 30],
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[30, 31],
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[31, 32],
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[32, 33],
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[33, 34],
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[34, 35],
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[35, 36],
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[36, 37],
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[37, 38],
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[38, 39],
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[39, 40],
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[40, 41],
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[41, 42],
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[42, 43],
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[43, 44],
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[44, 45],
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[45, 46],
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[46, 47],
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[47, 48],
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[48, 49],
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[49, 50],
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[50, 51],
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[51, 52],
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[52, 53],
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[53, 54],
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[54, 55],
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[55, 56],
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[56, 57],
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[57, 1],
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[57, 58],
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[38, 58],
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[58, 59],
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[59, 60],
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[60, 61],
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[61, 62],
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[62, 63],
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[63, 64],
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[64, 65],
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[65, 66],
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[66, 67],
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[67, 68],
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[69, 70],
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[70, 71],
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[71, 72],
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[72, 73],
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[73, 74],
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[74, 75],
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[75, 76],
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[76, 77],
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[77, 78],
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[59, 69],
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[78, 68],
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[79, 80],
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[80, 81],
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[81, 82],
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[82, 83],
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[83, 84],
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[84, 85],
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[85, 86],
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[86, 87],
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[87, 88],
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[58, 79],
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[88, 68],
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[69, 1],
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[37, 79],
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[41, 32], #новые
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[54, 6],
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[51, 12],
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[48, 19],
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[44, 25],
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[84, 64],
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[64, 74]]
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CAR_CATEGORIES_24 = ['karusel']
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CAR_SCORE_WEIGHTS_24 = [1.0]*len(CAR_KEYPOINTS_24)
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CAR_SIGMAS_24 = [0.05] * len(CAR_KEYPOINTS_24)
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CAR_POSE_24 = np.array([[-177.26242219, -152.48617537, 0. ],
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[-184.66727021, -125.83719367, 0. ],
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[-193.12308373, -98.24191839, 0. ],
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[-202.42051892, -73.69486768, 0. ],
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[-212.03196984, -43.15603975, 0. ],
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[-216.33625735, -18.34730925, 0. ],
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[-216.80303459, 9.66665368, 0. ],
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[-213.95990749, 31.84584727, 0. ],
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[-210.22282276, 56.07463589, 0. ],
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[-200.59863274, 82.61469931, 0. ],
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[-188.82017578, 106.26354604, 0. ],
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[-175.04445976, 130.01706468, 0. ],
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[-157.11721772, 150.98403855, 0. ],
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[-137.03570875, 169.05979572, 0. ],
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[-116.84952786, 185.13829382, 0. ],
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[ -97.40029673, 196.17130829, 0. ],
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[ -72.90558197, 206.46737301, 0. ],
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[ -47.2552298 , 213.81988508, 0. ],
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[ -11.46157442, 218.69986811, 0. ],
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[ 29.74391629, 215.85249464, 0. ],
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[ 60.12148998, 209.43353705, 0. ],
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[ 85.61058791, 200.75564061, 0. ],
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[ 106.21121008, 189.81880532, 0. ],
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[ 125.97021059, 175.83374547, 0. ],
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[ 145.833883 , 159.85142654, 0. ],
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[ 163.85730422, 140.76854711, 0. ],
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[ 181.03910377, 118.63744311, 0. ],
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[ 194.27872114, 95.29836575, 0. ],
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[ 202.57752678, 70.69897907, 0. ],
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[ 210.87633243, 46.0995924 , 0. ],
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[ 214.33899828, 18.24263734, 0. ],
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[ 215.54272527, -4.72584196, 0. ],
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[ 212.908942 , -30.89955369, 0. ],
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[ 207.22693416, -56.23164375, 0. ],
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[ 197.60274414, -82.77170718, 0. ],
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[ 186.92758863, -108.36547702, 0. ],
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[ 173.36121642, -136.1135138 , 0. ],
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[ 92.94749408, -130.31409495, 0. ],
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[ 89.74650802, -107.45028757, 0. ],
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[ 84.54826289, -84.69115209, 0. ],
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[ 78.35138822, -61.98435258, 0. ],
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[ 69.15862495, -39.43456093, 0. ],
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[ 58.96723214, -16.93710523, 0. ],
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[ 46.83091622, 4.45704901, 0. ],
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[ 27.91353738, 21.49033343, 0. ],
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[ 3.42306899, 30.22056582, 0. ],
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[ -18.38977291, 26.07328618, 0. ],
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[ -27.68720809, 50.6203369 , 0. ],
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[ -39.67500888, 30.96600831, 0. ],
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[ -52.66143919, 11.25934376, 0. ],
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[ -64.59690402, -9.39361436, 0. ],
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[ -75.53373931, -29.99423653, 0. ],
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[ -87.46920414, -50.64719466, 0. ],
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[ -96.30410845, -73.14040399, 0. ],
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[-104.14038323, -95.58127736, 0. ],
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[-110.97802847, -117.96981477, 0. ],
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[-115.81841464, -140.25368027, 0. ],
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[ -9.87599751, -212.80851645, 0. ],
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[-143.38258579, -244.83960891, 0. ],
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[-138.76003618, -256.6138195 , 0. ],
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[-135.03144419, -270.43762512, 0. ],
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[-130.30422266, -284.20909478, 0. ],
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[-127.52192425, -299.08386589, 0. ],
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[-123.79333226, -312.90767151, 0. ],
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[-119.11844669, -325.68051164, 0. ],
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[-116.38848423, -339.55665321, 0. ],
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[-112.55522032, -355.3777179 , 0. ],
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[-109.87759382, -368.25522994, 0. ],
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[-195.84742026, -294.65367464, 0. ],
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[-192.11882827, -308.47748026, 0. ],
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[-188.44257223, -321.30265634, 0. ],
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[-184.71398024, -335.12646196, 0. ],
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[-182.0886897 , -347.00534446, 0. ],
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[-179.4110632 , -359.8828565 , 0. ],
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[-175.73480716, -372.70803258, 0. ],
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[-173.10951662, -384.58691509, 0. ],
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[-170.43189012, -397.46442713, 0. ],
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[-167.75426362, -410.34193917, 0. ],
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[ 192.78072299, -258.26457915, 0. ],
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[ 188.46794275, -271.50844288, 0. ],
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[ 182.05323153, -282.85971946, 0. ],
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[ 177.74045128, -296.10358319, 0. ],
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[ 172.42904151, -309.39978288, 0. ],
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[ 168.11626126, -322.64364661, 0. ],
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[ 163.80348102, -335.88751034, 0. ],
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[ 159.49070078, -349.13137408, 0. ],
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[ 155.17792054, -362.37523781, 0. ],
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[ 151.91610578, -376.56539512, 0. ]])
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HFLIP_24 = {
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'1': '1',
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'2': '2',
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'3': '3',
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'4': '4',
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'5': '5',
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'6': '6',
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'7': '7',
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'8': '8',
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'9': '9',
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'10': '10',
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'11': '11',
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'12': '12',
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'13': '13',
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'14': '14',
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'15': '15',
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'16': '16',
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'17': '17',
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'18': '18',
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'19': '19',
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'20': '20',
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'21': '21',
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'22': '22'
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}
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training_weights_local_centrality = [
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0.890968488270775,
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0.716506138617812,
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1.05674590410869,
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0.764774195768455,
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0.637682585483328,
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0.686680807728366,
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0.955422595797394,
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0.936714585642375,
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1.34823795445326,
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1.38308992581967,
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1.32689945125819,
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1.38838655605483,
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1.18980184904613,
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1.02584355494795,
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0.90969156732068,
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1.24732068576104,
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1.11338768064342,
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0.933815217550391,
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0.852297518872114,
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1.04167641424727,
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1.01668968075247,
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1.34625964088011,
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0.911796331039028,
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0.866206536337413,
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1.55957820407853,
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0.730844382675724,
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0.651138644197359,
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0.758018559633786,
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1.31842501396691,
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1.32186116654782,
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0.744347016851606,
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0.636390683664723,
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0.715244950821949,
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1.63122349407032,
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0.849835699185461,
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0.910488007220499,
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1.44244151650561,
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1.14150437331681,
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1.19808610191343,
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0.960186788642886,
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1.05023623286937,
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1.19761709710598,
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1.3872216313401,
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1.01256700741214,
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1.1167909667759,
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1.27893496336199,
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1.54475684725655,
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1.40343733870633,
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1.45552060866114,
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1.47264222155031,
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0.970060423999993,
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0.944450314768933,
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0.623987071240172,
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0.5745237907704,
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0.66890646050993,
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0.978411632994504,
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0.587396395188292,
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0.76307999741129,
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0.609793563449648,
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0.67983566494545,
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0.685883538168462,
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0.753587600664775,
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0.770335133588157,
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0.764713638033368,
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0.792364155965385,
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0.796435233566833
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]
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def get_constants(num_kps):
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if num_kps == 24:
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CAR_POSE_24[:, 2] = 2.0
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return [CAR_KEYPOINTS_24, CAR_SKELETON_24, HFLIP_24, CAR_SIGMAS_24,
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CAR_POSE_24, CAR_CATEGORIES_24, CAR_SCORE_WEIGHTS_24]
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if num_kps == 66:
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CAR_POSE_66[:, 2] = 2.0
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return [CAR_KEYPOINTS_66, CAR_SKELETON_66, HFLIP_66, CAR_SIGMAS_66,
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CAR_POSE_66, CAR_CATEGORIES_66, CAR_SCORE_WEIGHTS_66]
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# using no if-elif-else construction due to pylint no-else-return error
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raise Exception("Only poses with 24 or 66 keypoints are available.")
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def draw_ann(ann, *, keypoint_painter, filename=None, margin=0.5, aspect=None, **kwargs):
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from openpifpaf import show # pylint: disable=import-outside-toplevel
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bbox = ann.bbox()
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xlim = bbox[0] - margin, bbox[0] + bbox[2] + margin
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ylim = bbox[1] - margin, bbox[1] + bbox[3] + margin
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if aspect == 'equal':
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fig_w = 5.0
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else:
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fig_w = 5.0 / (ylim[1] - ylim[0]) * (xlim[1] - xlim[0])
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with show.canvas(filename, figsize=(fig_w, 5), nomargin=True, **kwargs) as ax:
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ax.set_axis_off()
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ax.set_xlim(*xlim)
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ax.set_ylim(*ylim)
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if aspect is not None:
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ax.set_aspect(aspect)
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keypoint_painter.annotation(ax, ann)
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def draw_skeletons(pose, sigmas, skel, kps, scr_weights):
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from openpifpaf.annotation import Annotation # pylint: disable=import-outside-toplevel
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from openpifpaf import show # pylint: disable=import-outside-toplevel
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scale = np.sqrt(
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(np.max(pose[:, 0]) - np.min(pose[:, 0]))
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* (np.max(pose[:, 1]) - np.min(pose[:, 1]))
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)
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show.KeypointPainter.show_joint_scales = True
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keypoint_painter = show.KeypointPainter()
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ann = Annotation(keypoints=kps, skeleton=skel, score_weights=scr_weights)
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ann.set(pose, np.array(sigmas) * scale)
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os.makedirs('docs', exist_ok=True)
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draw_ann(ann, filename='docs/skeleton_car.png', keypoint_painter=keypoint_painter)
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def plot3d_red(ax_2D, p3d, skeleton):
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skeleton = [(bone[0] - 1, bone[1] - 1) for bone in skeleton]
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rot_p90_x = np.array([[1, 0, 0], [0, 0, 1], [0, 1, 0]])
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p3d = p3d @ rot_p90_x
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fig = ax_2D.get_figure()
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ax = Axes3D(fig, auto_add_to_figure=False)
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fig.add_axes(ax)
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ax.set_axis_off()
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ax_2D.set_axis_off()
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ax.view_init(azim=-90, elev=20)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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max_range = np.array([p3d[:, 0].max() - p3d[:, 0].min(),
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p3d[:, 1].max() - p3d[:, 1].min(),
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p3d[:, 2].max() - p3d[:, 2].min()]).max() / 2.0
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mid_x = (p3d[:, 0].max() + p3d[:, 0].min()) * 0.5
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mid_y = (p3d[:, 1].max() + p3d[:, 1].min()) * 0.5
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mid_z = (p3d[:, 2].max() + p3d[:, 2].min()) * 0.5
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ax.set_xlim(mid_x - max_range, mid_x + max_range)
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ax.set_ylim(mid_y - max_range, mid_y + max_range)
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ax.set_zlim(mid_z - max_range, mid_z + max_range) # pylint: disable=no-member
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for ci, bone in enumerate(skeleton):
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c = mplcm.get_cmap('tab20')((ci % 20 + 0.05) / 20) # Same coloring as Pifpaf preds
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ax.plot(p3d[bone, 0], p3d[bone, 1], p3d[bone, 2], color=c)
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def animate(i):
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ax.view_init(elev=10., azim=i)
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return fig
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return FuncAnimation(fig, animate, frames=360, interval=100)
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def print_associations():
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print("\nAssociations of the car skeleton with 24 keypoints")
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for j1, j2 in CAR_SKELETON_24:
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print(CAR_KEYPOINTS_24[j1 - 1], '-', CAR_KEYPOINTS_24[j2 - 1])
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print("\nAssociations of the car skeleton with 66 keypoints")
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for j1, j2 in CAR_SKELETON_66:
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print(CAR_KEYPOINTS_66[j1 - 1], '-', CAR_KEYPOINTS_66[j2 - 1])
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def main():
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# print_associations()
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# =============================================================================
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# draw_skeletons(CAR_POSE_24, sigmas = CAR_SIGMAS_24, skel = CAR_SKELETON_24,
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# kps = CAR_KEYPOINTS_24, scr_weights = CAR_SCORE_WEIGHTS_24)
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# draw_skeletons(CAR_POSE_66, sigmas = CAR_SIGMAS_66, skel = CAR_SKELETON_66,
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# kps = CAR_KEYPOINTS_66, scr_weights = CAR_SCORE_WEIGHTS_66)
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# =============================================================================
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# with openpifpaf.show.Canvas.blank(nomargin=True) as ax_2D:
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# anim_66 = plot3d_red(ax_2D, CAR_POSE_66, CAR_SKELETON_66)
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# anim_66.save('./CAR_66_Pose.gif', fps=30)
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with openpifpaf.show.Canvas.blank(nomargin=True) as ax_2D:
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anim_24 = plot3d_red(ax_2D, CAR_POSE_24, CAR_SKELETON_24)
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anim_24.save('./CAR_24_Pose.gif', fps=30)
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if __name__ == '__main__':
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main() |