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from models.rotation2xyz import Rotation2xyz
import numpy as np
from trimesh import Trimesh
import os
os.environ['PYOPENGL_PLATFORM'] = "osmesa"
import torch
from visualize.simplify_loc2rot import joints2smpl
import pyrender
import matplotlib.pyplot as plt
import io
import imageio
from shapely import geometry
import trimesh
from pyrender.constants import RenderFlags
import math
# import ffmpeg
from PIL import Image
class WeakPerspectiveCamera(pyrender.Camera):
def __init__(self,
scale,
translation,
znear=pyrender.camera.DEFAULT_Z_NEAR,
zfar=None,
name=None):
super(WeakPerspectiveCamera, self).__init__(
znear=znear,
zfar=zfar,
name=name,
)
self.scale = scale
self.translation = translation
def get_projection_matrix(self, width=None, height=None):
P = np.eye(4)
P[0, 0] = self.scale[0]
P[1, 1] = self.scale[1]
P[0, 3] = self.translation[0] * self.scale[0]
P[1, 3] = -self.translation[1] * self.scale[1]
P[2, 2] = -1
return P
def render(motions, outdir='test_vis', device_id=0, name=None, pred=True):
frames, njoints, nfeats = motions.shape
MINS = motions.min(axis=0).min(axis=0)
MAXS = motions.max(axis=0).max(axis=0)
height_offset = MINS[1]
motions[:, :, 1] -= height_offset
trajec = motions[:, 0, [0, 2]]
j2s = joints2smpl(num_frames=frames, device_id=0, cuda=True)
rot2xyz = Rotation2xyz(device=torch.device("cuda:0"))
faces = rot2xyz.smpl_model.faces
if (not os.path.exists(outdir + name+'_pred.pt') and pred) or (not os.path.exists(outdir + name+'_gt.pt') and not pred):
print(f'Running SMPLify, it may take a few minutes.')
motion_tensor, opt_dict = j2s.joint2smpl(motions) # [nframes, njoints, 3]
vertices = rot2xyz(torch.tensor(motion_tensor).clone(), mask=None,
pose_rep='rot6d', translation=True, glob=True,
jointstype='vertices',
vertstrans=True)
if pred:
torch.save(vertices, outdir + name+'_pred.pt')
else:
torch.save(vertices, outdir + name+'_gt.pt')
else:
if pred:
vertices = torch.load(outdir + name+'_pred.pt')
else:
vertices = torch.load(outdir + name+'_gt.pt')
frames = vertices.shape[3] # shape: 1, nb_frames, 3, nb_joints
print (vertices.shape)
MINS = torch.min(torch.min(vertices[0], axis=0)[0], axis=1)[0]
MAXS = torch.max(torch.max(vertices[0], axis=0)[0], axis=1)[0]
# vertices[:,:,1,:] -= MINS[1] + 1e-5
out_list = []
minx = MINS[0] - 0.5
maxx = MAXS[0] + 0.5
minz = MINS[2] - 0.5
maxz = MAXS[2] + 0.5
polygon = geometry.Polygon([[minx, minz], [minx, maxz], [maxx, maxz], [maxx, minz]])
polygon_mesh = trimesh.creation.extrude_polygon(polygon, 1e-5)
vid = []
for i in range(frames):
if i % 10 == 0:
print(i)
mesh = Trimesh(vertices=vertices[0, :, :, i].squeeze().tolist(), faces=faces)
base_color = (0.11, 0.53, 0.8, 0.5)
## OPAQUE rendering without alpha
## BLEND rendering consider alpha
material = pyrender.MetallicRoughnessMaterial(
metallicFactor=0.7,
alphaMode='OPAQUE',
baseColorFactor=base_color
)
mesh = pyrender.Mesh.from_trimesh(mesh, material=material)
polygon_mesh.visual.face_colors = [0, 0, 0, 0.21]
polygon_render = pyrender.Mesh.from_trimesh(polygon_mesh, smooth=False)
bg_color = [1, 1, 1, 0.8]
scene = pyrender.Scene(bg_color=bg_color, ambient_light=(0.4, 0.4, 0.4))
sx, sy, tx, ty = [0.75, 0.75, 0, 0.10]
camera = pyrender.PerspectiveCamera(yfov=(np.pi / 3.0))
light = pyrender.DirectionalLight(color=[1,1,1], intensity=300)
scene.add(mesh)
c = np.pi / 2
scene.add(polygon_render, pose=np.array([[ 1, 0, 0, 0],
[ 0, np.cos(c), -np.sin(c), MINS[1].cpu().numpy()],
[ 0, np.sin(c), np.cos(c), 0],
[ 0, 0, 0, 1]]))
light_pose = np.eye(4)
light_pose[:3, 3] = [0, -1, 1]
scene.add(light, pose=light_pose.copy())
light_pose[:3, 3] = [0, 1, 1]
scene.add(light, pose=light_pose.copy())
light_pose[:3, 3] = [1, 1, 2]
scene.add(light, pose=light_pose.copy())
c = -np.pi / 6
scene.add(camera, pose=[[ 1, 0, 0, (minx+maxx).cpu().numpy()/2],
[ 0, np.cos(c), -np.sin(c), 1.5],
[ 0, np.sin(c), np.cos(c), max(4, minz.cpu().numpy()+(1.5-MINS[1].cpu().numpy())*2, (maxx-minx).cpu().numpy())],
[ 0, 0, 0, 1]
])
# render scene
r = pyrender.OffscreenRenderer(960, 960)
color, _ = r.render(scene, flags=RenderFlags.RGBA)
# Image.fromarray(color).save(outdir+name+'_'+str(i)+'.png')
vid.append(color)
r.delete()
out = np.stack(vid, axis=0)
if pred:
imageio.mimsave(outdir + name+'_pred.gif', out, fps=20)
else:
imageio.mimsave(outdir + name+'_gt.gif', out, fps=20)
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--filedir", type=str, default='/CV/xhr/xhr_project/Paper/text2Pose/t2m/T2M-GPT-main/visualization/pose_np', help='motion npy file dir')
parser.add_argument('--motion-list', default=None, nargs="1", type=str, help="motion name list")
args = parser.parse_args()
filename_list = args.motion_list
filedir = args.filedir
for filename in filename_list:
motions = np.load(filedir + filename+'.npy')
print('pred', motions.shape, filename)
render(motions[0], outdir=filedir, device_id=0, name=filename, pred=True)
# motions = np.load(filedir + filename+'_pred.npy')
# print('pred', motions.shape, filename)
# render(motions[0], outdir=filedir, device_id=0, name=filename, pred=True)
# motions = np.load(filedir + filename+'_gt.npy')
# print('gt', motions.shape, filename)
# render(motions[0], outdir=filedir, device_id=0, name=filename, pred=False)