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config.py
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config.py
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r"""
Config for paths, joint set, and normalizing scales.
"""
# datasets (directory names) in AMASS
# e.g., for ACCAD, the path should be `paths.raw_amass_dir/ACCAD/ACCAD/s001/*.npz`
amass_data = ['HumanEva', 'MPI_HDM05', 'SFU', 'MPI_mosh', 'Transitions_mocap', 'SSM_synced', 'CMU',
'TotalCapture', 'Eyes_Japan_Dataset', 'KIT', 'BMLmovi', 'EKUT', 'TCD_handMocap', 'ACCAD',
'BioMotionLab_NTroje', 'BMLhandball', 'MPI_Limits', 'DFaust67']
class paths:
raw_amass_dir = 'data/dataset_raw/AMASS' # raw AMASS dataset path (raw_amass_dir/ACCAD/ACCAD/s001/*.npz)
amass_dir = 'data/dataset_work/AMASS' # output path for the synthetic AMASS dataset
raw_dipimu_dir = 'data/dataset_raw/DIP_IMU' # raw DIP-IMU dataset path (raw_dipimu_dir/s_01/*.pkl)
dipimu_dir = 'data/dataset_work/DIP_IMU' # output path for the preprocessed DIP-IMU dataset
# DIP recalculates the SMPL poses for TotalCapture dataset. You should acquire the pose data from the DIP authors.
raw_totalcapture_dip_dir = 'data/dataset_raw/TotalCapture/DIP_recalculate' # contain ground-truth SMPL pose (*.pkl)
raw_totalcapture_official_dir = 'data/dataset_raw/TotalCapture/official' # contain official gt (S1/acting1/gt_skel_gbl_pos.txt)
totalcapture_dir = 'data/dataset_work/TotalCapture' # output path for the preprocessed TotalCapture dataset
example_dir = 'data/example' # example IMU measurements
smpl_file = 'models/SMPL_male.pkl' # official SMPL model path
weights_file = 'data/weights.pt' # network weight file
class joint_set:
leaf = [7, 8, 12, 20, 21]
full = list(range(1, 24))
reduced = [1, 2, 3, 4, 5, 6, 9, 12, 13, 14, 15, 16, 17, 18, 19]
ignored = [0, 7, 8, 10, 11, 20, 21, 22, 23]
lower_body = [0, 1, 2, 4, 5, 7, 8, 10, 11]
lower_body_parent = [None, 0, 0, 1, 2, 3, 4, 5, 6]
n_leaf = len(leaf)
n_full = len(full)
n_reduced = len(reduced)
n_ignored = len(ignored)
acc_scale = 30
vel_scale = 3