body-pose-animation/model.py
2021-02-08 21:03:19 +01:00

157 lines
4.8 KiB
Python

import matplotlib.pyplot as plt
import torch
import numpy as np
import smplx
import os
from human_body_prior.body_model.body_model_vposer import BodyModelWithPoser
from human_body_prior.tools.model_loader import load_vposer
def get_model_path(type, gender, dir):
return os.path.join(
dir,
type,
type.upper() + "_" +
gender.upper() + ".npz")
def get_model_path_from_conf(config):
return get_model_path(
config['smpl']['type'],
config['smpl']['gender'],
config['smpl']['modelRootDir']
)
class VPoserModel():
global_vposer = None
def __init__(
self,
model_type='smpl',
body_model_path="./models/smplx/SMPLX_MALE.npz",
vposer_model_path="./vposer_v1_0",
ext='npz',
gender='neutral',
create_body_pose=True,
plot_joints=True,
num_betas=10,
sample_shape=False,
sample_expression=False,
num_expression_coeffs=10,
use_vposer=True
):
self.body_model_path = body_model_path
self.vposer_model_path = vposer_model_path
self.model_type = model_type
self.ext = ext
self.gender = gender
self.plot_joints = plot_joints
self.num_betas = num_betas
self.sample_shape = sample_shape
self.sample_expression = sample_expression
self.num_expression_coeffs = num_expression_coeffs
self.create_body_pose = create_body_pose
self.use_vposer = use_vposer
self.create_model()
def create_model(self):
self.model = BodyModelWithPoser(
bm_path=self.body_model_path,
batch_size=1,
poser_type="vposer",
smpl_exp_dir=self.vposer_model_path
)
return self.model
def get_vposer_latent(self):
return self.model.poZ_body
def get_pose(self):
return self.model.pose_body
def from_conf(config, use_global=True):
model_path = get_model_path_from_conf(config)
if VPoserModel.global_vposer is None:
VPoserModel.global_vposer = VPoserModel(
model_type=config['smpl']['type'],
gender=config['smpl']['gender'],
vposer_model_path=config['pose']['vposerPath'],
body_model_path=model_path)
return VPoserModel.global_vposer
class SMPLyModel():
def __init__(
self,
model_folder,
model_type='smplx',
ext='npz',
gender='male',
create_body_pose=True,
plot_joints=True,
num_betas=10,
sample_shape=False,
sample_expression=True,
num_expression_coeffs=10,
use_face_contour=False,
use_vposer_init=False,
device=torch.device('cpu')
):
self.model_folder = model_folder
self.model_type = model_type
self.ext = ext
self.gender = gender
self.plot_joints = plot_joints
self.num_betas = num_betas
self.sample_shape = sample_shape
self.sample_expression = sample_expression
self.num_expression_coeffs = num_expression_coeffs
self.use_face_contour = use_face_contour
self.create_body_pose = create_body_pose
self.use_vposer_init = use_vposer_init
self.device = device
def create_model(self, initial_pose=None):
if self.use_vposer_init:
# sample a valid human shape via vposer
vp, ps = load_vposer("./vposer_v1_0")
vp = vp.to(device=self.device)
self.vp = vp
self.vposer_sample = torch.from_numpy(
np.random.randn(1, 32).astype(np.float32)).to(device=self.device)
# sample SMPL body pose from vposer
initial_pose = self.vp.decode(
self.vposer_sample, output_type='aa').view(-1, 63)
self.model = smplx.create(
self.model_folder,
model_type=self.model_type,
gender=self.gender,
body_pose=initial_pose,
use_face_contour=self.use_face_contour,
create_body_pose=self.create_body_pose,
num_betas=self.num_betas,
return_verts=True,
num_expression_coeffs=self.num_expression_coeffs,
ext=self.ext)
return self.model
def from_config(config, device=None, dtype=None):
return SMPLyModel(
model_folder=config['smpl']['modelRootDir'],
gender=config['smpl']['gender'],
model_type=config['smpl']['type'],
ext=config['smpl']['ext'],
use_vposer_init=config['smpl']['useVposerInit'],
device=device
)
def model_from_conf(config, device=None, dtype=None, initial_pose=None):
return SMPLyModel.from_config(config, device=device, dtype=dtype).create_model(initial_pose=initial_pose)