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import imageio
import matplotlib
from ops.utils import *
from ops.gs.basic import *
from ops.trajs import _generate_trajectory
class Check():
def __init__(self) -> None:
pass
def _visual_pcd(self,scene:Gaussian_Scene):
xyzs,rgbs = [],[]
for i,gf in enumerate(scene.gaussian_frames):
xyz = gf.xyz.detach().cpu().numpy()
rgb = torch.sigmoid(gf.rgb).detach().cpu().numpy()
opacity = gf.opacity.detach().squeeze().cpu().numpy() > 1e-5
xyzs.append(xyz[opacity])
rgbs.append(rgb[opacity])
xyzs = np.concatenate(xyzs,axis=0)
rgbs = np.concatenate(rgbs,axis=0)
visual_pcd(xyzs,color=rgbs,normal=True)
@torch.no_grad()
def _render_video(self,scene:Gaussian_Scene,save_dir='./'):
# render 5times frames
nframes = len(scene.frames)*25
video_trajs = _generate_trajectory(None,scene,nframes=nframes)
H,W,intrinsic = scene.frames[0].H,scene.frames[0].W,deepcopy(scene.frames[0].intrinsic)
if H<W:
if H>512:
ratio = 512/H
W,H = int(W*ratio),int(H*ratio)
intrinsic[0:2] = intrinsic[0:2]*ratio
else:
if W>512:
ratio = 512/W
W,H = int(W*ratio),int(H*ratio)
intrinsic[0:2] = intrinsic[0:2]*ratio
# render
rgbs,dpts = [],[]
print(f'[INFO] rendering final video with {nframes} frames...')
for pose in video_trajs:
frame = Frame(H=H,W=W,
intrinsic=intrinsic,
extrinsic=pose)
rgb,dpt,alpha = scene._render_RGBD(frame)
rgb = rgb.detach().float().cpu().numpy()
dpt = dpt.detach().float().cpu().numpy()
dpts.append(dpt)
rgbs.append((rgb * 255).astype(np.uint8))
rgbs = np.stack(rgbs, axis=0)
dpts = np.stack(dpts, axis=0)
valid_dpts = dpts[dpts>0.]
_min = np.percentile(valid_dpts, 1)
_max = np.percentile(valid_dpts,99)
dpts = (dpts-_min) / (_max-_min)
dpts = dpts.clip(0,1)
cm = matplotlib.colormaps["plasma"]
dpts_color = cm(dpts,bytes=False)[...,0:3]
dpts_color = (dpts_color*255).astype(np.uint8)
imageio.mimwrite(f'{save_dir}video_rgb.mp4',rgbs,fps=20)
imageio.mimwrite(f'{save_dir}video_dpt.mp4',dpts_color,fps=20)
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