config.py

import torch
import numpy as np
import math
import os

device = torch.device('cuda:0')

# SMPL related
cano_smpl_pose = np.zeros(75, dtype = np.float32)
cano_smpl_pose[3+3*1+2] = math.radians(25)
cano_smpl_pose[3+3*2+2] = math.radians(-25)
cano_smpl_pose = torch.from_numpy(cano_smpl_pose)
cano_smpl_transl = cano_smpl_pose[:3]
cano_smpl_global_orient = cano_smpl_pose[3:6]
cano_smpl_body_pose = cano_smpl_pose[6:69]

# fist pose
left_hand_pose = torch.tensor([0.09001956135034561, 0.1604590266942978, -0.3295670449733734, 0.12445037066936493, -0.11897698789834976, -1.5051144361495972, -0.1194705069065094, -0.16281449794769287, -0.6292539834976196, -0.27713727951049805, 0.035170216113328934, -0.5893177390098572, -0.20759613811969757, 0.07492011040449142, -1.4485805034637451, -0.017797302454710007, -0.12478633224964142, -0.7844052314758301, -0.4157009720802307, -0.5140947103500366, -0.2961726784706116, -0.7421528100967407, -0.11505582183599472, -0.7972996830940247, -0.29345276951789856, -0.18898937106132507, -0.6230823397636414, -0.18764786422252655, -0.2696149945259094, -0.5542467832565308, -0.47717514634132385, -0.12663133442401886, -1.2747308015823364, -0.23940050601959229, -0.1586960405111313, -0.7655659914016724, 0.8745182156562805, 0.5848557353019714, -0.07204405218362808, -0.5052485466003418, 0.1797526329755783, 0.3281439244747162, 0.5276764035224915, -0.008714836090803146, -0.4373648762702942], dtype = torch.float32)
right_hand_pose = torch.tensor([0.034751810133457184, -0.12605343759059906, 0.5510415434837341, 0.19454114139080048, 0.11147838830947876, 1.4676157236099243, -0.14799435436725616, 0.17293521761894226, 0.4679432511329651, -0.3042353689670563, 0.007868679240345955, 0.8570928573608398, -0.1827319711446762, -0.07225851714611053, 1.307037591934204, -0.02989627793431282, 0.1208646297454834, 0.7142824530601501, -0.3403030335903168, 0.5368582606315613, 0.3839572072029114, -0.9722614884376526, 0.17358140647411346, 0.911861002445221, -0.29665058851242065, 0.21779759228229523, 0.7269846796989441, -0.15343312919139862, 0.3083758056163788, 0.7146623730659485, -0.5153037309646606, 0.1721675992012024, 1.2982604503631592, -0.2590428292751312, 0.12812566757202148, 0.7502076029777527, 0.8694817423820496, -0.5263001322746277, 0.06934576481580734, -0.4630220830440521, -0.19237111508846283, -0.25436165928840637, 0.5972414612770081, -0.08250168710947037, 0.5013565421104431], dtype = torch.float32)


# project
PROJ_DIR = os.path.dirname(os.path.realpath(__file__))

opt = dict()


def load_global_opt(path):
    import yaml
    global opt
    opt = yaml.load(open(path, encoding = 'UTF-8'), Loader = yaml.FullLoader)