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# Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import numpy as np
import torch
from mmpose.models.utils import SMPL
from tests.utils.mesh_utils import generate_smpl_weight_file
def test_smpl():
"""Test smpl model."""
# build smpl model
smpl = None
with tempfile.TemporaryDirectory() as tmpdir:
# generate weight file for SMPL model.
generate_smpl_weight_file(tmpdir)
smpl_cfg = dict(
smpl_path=tmpdir,
joints_regressor=osp.join(tmpdir, 'test_joint_regressor.npy'))
smpl = SMPL(**smpl_cfg)
assert smpl is not None, 'Fail to build SMPL model'
# test get face function
faces = smpl.get_faces()
assert isinstance(faces, np.ndarray)
betas = torch.zeros(3, 10)
body_pose = torch.zeros(3, 23 * 3)
global_orient = torch.zeros(3, 3)
transl = torch.zeros(3, 3)
gender = torch.LongTensor([-1, 0, 1])
# test forward with body_pose and global_orient in axis-angle format
smpl_out = smpl(
betas=betas, body_pose=body_pose, global_orient=global_orient)
assert isinstance(smpl_out, dict)
assert smpl_out['vertices'].shape == torch.Size([3, 6890, 3])
assert smpl_out['joints'].shape == torch.Size([3, 24, 3])
# test forward with body_pose and global_orient in rotation matrix format
body_pose = torch.eye(3).repeat([3, 23, 1, 1])
global_orient = torch.eye(3).repeat([3, 1, 1, 1])
_ = smpl(betas=betas, body_pose=body_pose, global_orient=global_orient)
# test forward with translation
_ = smpl(
betas=betas,
body_pose=body_pose,
global_orient=global_orient,
transl=transl)
# test forward with gender
_ = smpl(
betas=betas,
body_pose=body_pose,
global_orient=global_orient,
transl=transl,
gender=gender)
# test forward when all samples in the same gender
gender = torch.LongTensor([0, 0, 0])
_ = smpl(
betas=betas,
body_pose=body_pose,
global_orient=global_orient,
transl=transl,
gender=gender)
# test forward when batch size = 0
_ = smpl(
betas=torch.zeros(0, 10),
body_pose=torch.zeros(0, 23 * 3),
global_orient=torch.zeros(0, 3))
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