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import os.path as osp
import argparse
import numpy as np
import torch
import pyrender
import trimesh
import smplx
from tqdm.auto import tqdm, trange
from pathlib import Path
def main(model_folder,
motion_file,
model_type='smplx',
ext='npz',
gender='neutral',
plot_joints=False,
num_betas=10,
sample_expression=True,
num_expression_coeffs=10,
use_face_contour=False):
# open motion file
motion = np.load(motion_file, allow_pickle=True)
_motion = {}
for k,v in motion.items():
if isinstance(v, np.ndarray):
print(k, motion[k].shape, motion[k].dtype)
if motion[k].dtype in ("<U7", "<U5", "<U4", "object", "|S7"):
_motion[k] = str(motion[k])
else:
_motion[k] = torch.from_numpy(motion[k]).float()
else:
print(k, v)
_motion[k] = v
motion = _motion
if "poses" in motion:
motion["global_orient"] = motion["root_orient"]
motion["body_pose"] = motion["pose_body"] # seriously?
motion["left_hand_pose"] = motion["pose_hand"][:,:45]
motion["right_hand_pose"] = motion["pose_hand"][:,45:]
num_betas = len(motion['betas'])
gender = str(motion['gender'])
model = smplx.create(model_folder, model_type=model_type,
gender=gender, use_face_contour=use_face_contour,
num_betas=num_betas,
num_expression_coeffs=num_expression_coeffs,
use_pca=False,
ext=ext)
betas, expression = motion['betas'], None
betas = betas.unsqueeze(0)[:, :model.num_betas]
global_orient = motion['global_orient']
body_pose = motion['body_pose']
left_hand_pose = motion['left_hand_pose']
right_hand_pose = motion['right_hand_pose']
# if sample_expression:
# expression = torch.randn(
# [1, model.num_expression_coeffs], dtype=torch.float32)
#print(expression)
#print(betas.shape, body_pose.shape, expression.shape)
for pose_idx in trange(body_pose.size(0)):
pose_idx = [pose_idx]
# output = model(betas=betas, # expression=expression,
# return_verts=True)
# for x in [betas, global_orient, body_pose, left_hand_pose, right_hand_pose]:
# print(x.dtype, x.shape)
output = model(
betas=betas,
global_orient=global_orient[pose_idx],
body_pose=body_pose[pose_idx],
left_hand_pose=left_hand_pose[pose_idx],
right_hand_pose=right_hand_pose[pose_idx],
# expression=expression,
return_verts=True
)
vertices = output.vertices.detach().cpu().numpy().squeeze()
joints = output.joints.detach().cpu().numpy().squeeze()
vertex_colors = np.ones([vertices.shape[0], 4]) * [0.3, 0.3, 0.3, 0.8]
tri_mesh = trimesh.Trimesh(vertices, model.faces,
vertex_colors=vertex_colors)
mesh = pyrender.Mesh.from_trimesh(tri_mesh)
scene = pyrender.Scene()
scene.add(mesh)
if plot_joints:
sm = trimesh.creation.uv_sphere(radius=0.005)
sm.visual.vertex_colors = [0.9, 0.1, 0.1, 1.0]
tfs = np.tile(np.eye(4), (len(joints), 1, 1))
tfs[:, :3, 3] = joints
joints_pcl = pyrender.Mesh.from_trimesh(sm, poses=tfs)
scene.add(joints_pcl)
pyrender.Viewer(scene, use_raymond_lighting=True)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='SMPL-X Demo')
parser.add_argument('--model-folder', required=True, type=str,
help='The path to the model folder')
parser.add_argument('--motion-file', required=True, type=str,
help='The path to the motion file to process')
parser.add_argument('--num-expression-coeffs', default=10, type=int,
dest='num_expression_coeffs',
help='Number of expression coefficients.')
parser.add_argument('--ext', type=str, default='npz',
help='Which extension to use for loading')
parser.add_argument('--sample-expression', default=True,
dest='sample_expression',
type=lambda arg: arg.lower() in ['true', '1'],
help='Sample a random expression')
parser.add_argument('--use-face-contour', default=False,
type=lambda arg: arg.lower() in ['true', '1'],
help='Compute the contour of the face')
args = parser.parse_args()
def resolve(path):
return osp.expanduser(osp.expandvars(path))
model_folder = resolve(args.model_folder)
motion_file = resolve(args.motion_file)
ext = args.ext
num_expression_coeffs = args.num_expression_coeffs
sample_expression = args.sample_expression
main(model_folder, motion_file, ext=ext,
sample_expression=sample_expression,
use_face_contour=args.use_face_contour)
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