common/constants.py

from os.path import join

DIST_MATRIX_PATH = 'data/smpl/smpl_neutral_geodesic_dist.npy'
SMPL_MEAN_PARAMS = 'data/smpl_mean_params.npz'
SMPL_MODEL_DIR = 'data/smpl/'
SMPLX_MODEL_DIR = 'data/smplx/'

N_PARTS = 24

# Mean and standard deviation for normalizing input image
IMG_NORM_MEAN = [0.485, 0.456, 0.406]
IMG_NORM_STD = [0.229, 0.224, 0.225]

# Output folder to save test/train npz files
DATASET_NPZ_PATH = 'datasets/Release_Datasets'
CONTACT_MAPPING_PATH = 'data/conversions'

# Path to test/train npz files
DATASET_FILES = {
    'train': {
        'damon': join(DATASET_NPZ_PATH, 'damon/hot_dca_trainval.npz'),
        'rich': join(DATASET_NPZ_PATH, 'rich/rich_train_smplx_cropped_bmp.npz'),
        'prox': join(DATASET_NPZ_PATH, 'prox/prox_train_smplx_ds4.npz'),
    },
    'val': {
        'damon': join(DATASET_NPZ_PATH, 'damon/hot_dca_test.npz'),
        'rich': join(DATASET_NPZ_PATH, 'rich/rich_test_smplx_cropped_bmp.npz'),
        'prox': join(DATASET_NPZ_PATH, 'prox/prox_val_smplx_ds4.npz'),
    },
    'test': {
        'damon': join(DATASET_NPZ_PATH, 'damon/hot_dca_test.npz'),
        'rich': join(DATASET_NPZ_PATH, 'rich/rich_test_smplx_cropped_bmp.npz'),
        'prox': join(DATASET_NPZ_PATH, 'prox/prox_val_smplx_ds4.npz'),
    },
}