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import os
import torch
import numpy as np
import cv2
import matplotlib.pyplot as plt
import glob
import pickle
import pyrender
import trimesh
import smplx
from pathlib import Path
from shapely import geometry
from smplx import SMPL as _SMPL
from smplx.utils import SMPLOutput as ModelOutput
from scipy.spatial.transform.rotation import Rotation as RRR
class Renderer:
"""
Renderer used for visualizing the SMPL model
Code adapted from https://github.com/vchoutas/smplify-x
"""
def __init__(self, vertices, focal_length=5000, img_res=(224,224), faces=None):
self.renderer = pyrender.OffscreenRenderer(viewport_width=img_res[0],
viewport_height=img_res[1],
point_size=2.0)
self.focal_length = focal_length
self.camera_center = [img_res[0] // 2, img_res[1] // 2]
self.faces = faces
if torch.cuda.is_available():
self.device = torch.device("cuda")
else:
self.device = torch.device("cpu")
self.rot = trimesh.transformations.rotation_matrix(np.radians(180), [1, 0, 0])
minx, miny, minz = vertices.min(axis=(0, 1))
maxx, maxy, maxz = vertices.max(axis=(0, 1))
minx = minx - 0.5
maxx = maxx + 0.5
minz = minz - 0.5
maxz = maxz + 0.5
floor = geometry.Polygon([[minx, minz], [minx, maxz], [maxx, maxz], [maxx, minz]])
self.floor = trimesh.creation.extrude_polygon(floor, 1e-5)
self.floor.visual.face_colors = [0, 0, 0, 0.2]
self.floor.apply_transform(self.rot)
self.floor_pose =np.array([[ 1, 0, 0, 0],
[ 0, np.cos(np.pi / 2), -np.sin(np.pi / 2), miny],
[ 0, np.sin(np.pi / 2), np.cos(np.pi / 2), 0],
[ 0, 0, 0, 1]])
c = -np.pi / 6
self.camera_pose = [[ 1, 0, 0, (minx+maxx)/2],
[ 0, np.cos(c), -np.sin(c), 1.5],
[ 0, np.sin(c), np.cos(c), max(4, minz+(1.5-miny)*2, (maxx-minx))],
[ 0, 0, 0, 1]
]
def __call__(self, vertices, camera_translation):
floor_render = pyrender.Mesh.from_trimesh(self.floor, smooth=False)
material = pyrender.MetallicRoughnessMaterial(
metallicFactor=0.1,
alphaMode='OPAQUE',
baseColorFactor=(0.658, 0.214, 0.0114, 0.2))
mesh = trimesh.Trimesh(vertices, self.faces)
mesh.apply_transform(self.rot)
mesh = pyrender.Mesh.from_trimesh(mesh, material=material)
camera = pyrender.PerspectiveCamera(yfov=(np.pi / 3.0))
light = pyrender.DirectionalLight(color=[1,1,1], intensity=350)
spot_l = pyrender.SpotLight(color=np.ones(3), intensity=300.0,
innerConeAngle=np.pi/16, outerConeAngle=np.pi/6)
point_l = pyrender.PointLight(color=np.ones(3), intensity=300.0)
scene = pyrender.Scene(bg_color=(1.,1.,1.,0.8),ambient_light=(0.4, 0.4, 0.4))
scene.add(floor_render, pose=self.floor_pose)
scene.add(mesh, 'mesh')
light_pose = np.eye(4)
light_pose[:3, 3] = np.array([0, -1, 1])
scene.add(light, pose=light_pose)
light_pose[:3, 3] = np.array([0, 1, 1])
scene.add(light, pose=light_pose)
light_pose[:3, 3] = np.array([1, 1, 2])
scene.add(light, pose=light_pose)
scene.add(camera, pose=self.camera_pose)
flags = pyrender.RenderFlags.RGBA | pyrender.RenderFlags.SHADOWS_DIRECTIONAL
color, rend_depth = self.renderer.render(scene, flags=flags)
return color
class SMPLRender():
def __init__(self, SMPL_MODEL_DIR):
if torch.cuda.is_available():
self.device = torch.device("cuda")
else:
self.device = torch.device("cpu")
# self.smpl = SMPL(SMPL_MODEL_DIR, batch_size=1, create_transl=False).to(self.device)
self.smpl = smplx.create(Path(SMPL_MODEL_DIR).parent, model_type="smpl", gender="neutral", ext="npz", batch_size=1).to(self.device)
self.pred_camera_t = []
self.focal_length = 110
def init_renderer(self, res, smpl_param, is_headroot=False):
poses = smpl_param['pred_pose']
pred_rotmats = []
for pose in poses:
if pose.size==72:
pose = pose.reshape(-1,3)
pose = RRR.from_rotvec(pose).as_matrix()
pose = pose.reshape(1,24,3,3)
pred_rotmats.append(torch.from_numpy(pose.astype(np.float32)[None]).to(self.device))
pred_rotmat = torch.cat(pred_rotmats, dim=0)
pred_betas = torch.from_numpy(smpl_param['pred_shape'].reshape(1, 10).astype(np.float32)).to(self.device)
pred_root = torch.tensor(smpl_param['pred_root'].reshape(-1, 3).astype(np.float32),device=self.device)
smpl_output = self.smpl(betas=pred_betas, body_pose=pred_rotmat[:, 1:],transl=pred_root, global_orient=pred_rotmat[:, :1], pose2rot=False)
self.vertices = smpl_output.vertices.detach().cpu().numpy()
pred_root = pred_root[0]
if is_headroot:
pred_root = pred_root - smpl_output.joints[0,12].detach().cpu().numpy()
self.pred_camera_t.append(pred_root)
self.renderer = Renderer(vertices=self.vertices, focal_length=self.focal_length,
img_res=(res[1], res[0]), faces=self.smpl.faces)
def render(self, index):
renderImg = self.renderer(self.vertices[index, ...], self.pred_camera_t)
return renderImg
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