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render_pkl_body.py
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# -*- coding: utf-8 -*-
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# You can only use this computer program if you have closed
# a license agreement with MPG or you get the right to use the computer
# program from someone who is authorized to grant you that right.
# Any use of the computer program without a valid license is prohibited and
# liable to prosecution.
#
# Copyright©2019 Max-Planck-Gesellschaft zur Förderung
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
# for Intelligent Systems. All rights reserved.
#
# Contact: [email protected]
# Contact: Vassilis choutas, [email protected]
import os
import os.path as osp
import argparse
import pickle
import shutil
import torch
import smplx
import numpy as np
from cmd_parser import parse_config
from human_body_prior.tools.model_loader import load_vposer
from utils import JointMapper
import pyrender
import trimesh
def read_file_paths(file_path):
with open(file_path, 'r') as file:
paths = [line.strip() for line in file.readlines()]
return paths
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--pkl', nargs='+', type=str,
help='The pkl files that will be read')
parser.add_argument('--results', nargs='?', type=str,
help='The directory above the folder containing the pkl file to be read')
parser.add_argument('--display', nargs='?', type=str, const='No',
help='Enter "Yes" or "yes" to display')
args, remaining = parser.parse_known_args()
pkl_paths = args.pkl
results = args.results
whether_dis = args.display
if not pkl_paths:
pkl_paths = []
if not results:
parser.error('Either --pkl or --results must be provided.')
else:
for folder_name in os.listdir(results):
pkl_folder = os.path.join(results, folder_name)
# 确保是文件夹而不是文件
if os.path.isdir(pkl_folder):
pkl_file_path = os.path.join(pkl_folder, '000.pkl')
if os.path.exists(pkl_file_path):
pkl_paths.append(pkl_file_path)
args = parse_config(remaining)
dtype = torch.float32
use_cuda = args.get('use_cuda', True)
if use_cuda and torch.cuda.is_available():
device = torch.device('cuda')
else:
device = torch.device('cpu')
model_type = args.get('model_type', 'smplx')
print('Model type:', model_type)
print(args.get('model_folder'))
model_params = dict(model_path=args.get('model_folder'),
# joint_mapper=joint_mapper,
create_global_orient=True,
create_body_pose=not args.get('use_vposer'),
create_betas=True,
create_left_hand_pose=False,
create_right_hand_pose=False,
create_expression=False,
create_jaw_pose=False,
create_leye_pose=False,
create_reye_pose=False,
create_transl=False,
dtype=dtype,
**args)
model = smplx.create(**model_params)
model = model.to(device=device)
batch_size = args.get('batch_size', 1)
use_vposer = args.get('use_vposer', True)
vposer, pose_embedding = [None, ] * 2
vposer_ckpt = args.get('vposer_ckpt', '')
if use_vposer:
pose_embedding = torch.zeros([batch_size, 32],
dtype=dtype, device=device,
requires_grad=True)
vposer_ckpt = osp.expandvars(vposer_ckpt)
vposer, _ = load_vposer(vposer_ckpt, vp_model='snapshot')
vposer = vposer.to(device=device)
vposer.eval()
for pkl_path in pkl_paths:
with open(pkl_path, 'rb') as f:
data = pickle.load(f, encoding='latin1')
if use_vposer:
with torch.no_grad():
pose_embedding[:] = torch.tensor(
data['body_pose'], device=device, dtype=dtype)
est_params = {}
for key, val in data.items():
if key == 'body_pose' and use_vposer:
body_pose = vposer.decode(
pose_embedding, output_type='aa').view(1, -1)
if model_type == 'smpl':
wrist_pose = torch.zeros([body_pose.shape[0], 6],
dtype=body_pose.dtype,
device=body_pose.device)
body_pose = torch.cat([body_pose, wrist_pose], dim=1)
est_params['body_pose'] = body_pose
else:
est_params[key] = torch.tensor(val, dtype=dtype, device=device)
model_output = model(**est_params)
vertices = model_output.vertices.detach().cpu().numpy().squeeze()
joints = model_output.joints.detach().cpu().numpy().squeeze()
def write_joints_file(file_path, lines):
os.makedirs(os.path.dirname(file_path), exist_ok=True)
with open(file_path, 'w') as f:
f.writelines(lines)
def write_and_clear_joints_files(joints, body_joint_file_path, hand_joint_file_path, face_joint_file_path):
body_lines = []
hand_lines = []
face_lines = []
for i in range(joints.shape[0]):
x = joints[i, 0]
y = joints[i, 1]
z = joints[i, 2]
if i < 25 or (i >= 60 and i <= 65):
line = "身体关节点 {}: x={}, y={}, z={}\n".format(i, x, y, z)
body_lines.append(line)
if i == 21 or i == 20:
line = "手关节点 {}: x={}, y={}, z={}\n".format(i, x, y, z)
hand_lines.append(line)
elif (i >= 25 and i <= 54) or (i >= 66 and i <= 75):
line = "手关节点 {}: x={}, y={}, z={}\n".format(i, x, y, z)
hand_lines.append(line)
else:
line = "脸关节点 {}: x={}, y={}, z={}\n".format(i, x, y, z)
face_lines.append(line)
write_joints_file(body_joint_file_path, body_lines)
write_joints_file(hand_joint_file_path, hand_lines)
write_joints_file(face_joint_file_path, face_lines)
print("关节点坐标已成功写入到记事本文件：")
print("身体关节点：{}".format(body_joint_file_path))
print("手关节点：{}".format(hand_joint_file_path))
print("脸关节点：{}".format(face_joint_file_path))
pkl_dir_name = os.path.dirname(pkl_path)
pkl_base_name = os.path.basename(pkl_dir_name)
body_joint_file_path = "./joints_output/{}/body_joints.txt".format(pkl_base_name)
hand_joint_file_path = "./joints_output/{}/hand_joints.txt".format(pkl_base_name)
face_joint_file_path = "./joints_output/{}/face_joints.txt".format(pkl_base_name)
write_and_clear_joints_files(joints, body_joint_file_path, hand_joint_file_path, face_joint_file_path)
out_mesh = trimesh.Trimesh(vertices, model.faces, process=False)
material = pyrender.MetallicRoughnessMaterial(
metallicFactor=0.0,
alphaMode='OPAQUE',
baseColorFactor=(1.0, 1.0, 0.9, 1.0))
mesh = pyrender.Mesh.from_trimesh(
out_mesh,
material=material)
scene = pyrender.Scene(bg_color=[0.0, 0.0, 0.0, 0.0],
ambient_light=(0.3, 0.3, 0.3))
# 注释掉展示整体人体模型的代码：
# scene.add(mesh, 'mesh')
# 添加展示身体关节点的代码：
if whether_dis == "Yes" or whether_dis == "yes":
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))
# 修改关节数量，只保留身体关节点：
num_body_joints = 25
tfs = tfs[:num_body_joints + 6, :]
tfs[:num_body_joints, :3, 3] = joints[:num_body_joints, :]
tfs[num_body_joints:num_body_joints + 6, :3, 3] = joints[60:66, :]
joints_pcl = pyrender.Mesh.from_trimesh(sm, poses=tfs)
scene.add(joints_pcl)
pyrender.Viewer(scene, use_raymond_lighting=True)