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Running
on
Zero
File size: 5,555 Bytes
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import torch
import numpy as np
from tqdm import tqdm
import utils3d
from PIL import Image
from ..renderers import OctreeRenderer, GaussianRenderer, MeshRenderer
from ..representations import Octree, Gaussian, MeshExtractResult
from ..modules import sparse as sp
from .random_utils import sphere_hammersley_sequence
def yaw_pitch_r_fov_to_extrinsics_intrinsics(yaws, pitchs, rs, fovs):
is_list = isinstance(yaws, list)
if not is_list:
yaws = [yaws]
pitchs = [pitchs]
if not isinstance(rs, list):
rs = [rs] * len(yaws)
if not isinstance(fovs, list):
fovs = [fovs] * len(yaws)
extrinsics = []
intrinsics = []
for yaw, pitch, r, fov in zip(yaws, pitchs, rs, fovs):
fov = torch.deg2rad(torch.tensor(float(fov))).cuda()
yaw = torch.tensor(float(yaw)).cuda()
pitch = torch.tensor(float(pitch)).cuda()
orig = torch.tensor([
torch.sin(yaw) * torch.cos(pitch),
torch.cos(yaw) * torch.cos(pitch),
torch.sin(pitch),
]).cuda() * r
extr = utils3d.torch.extrinsics_look_at(orig, torch.tensor([0, 0, 0]).float().cuda(), torch.tensor([0, 0, 1]).float().cuda())
intr = utils3d.torch.intrinsics_from_fov_xy(fov, fov)
extrinsics.append(extr)
intrinsics.append(intr)
if not is_list:
extrinsics = extrinsics[0]
intrinsics = intrinsics[0]
return extrinsics, intrinsics
def render_frames(sample, extrinsics, intrinsics, options={}, colors_overwrite=None, verbose=True, **kwargs):
if isinstance(sample, Octree):
renderer = OctreeRenderer()
renderer.rendering_options.resolution = options.get('resolution', 512)
renderer.rendering_options.near = options.get('near', 0.8)
renderer.rendering_options.far = options.get('far', 1.6)
renderer.rendering_options.bg_color = options.get('bg_color', (0, 0, 0))
renderer.rendering_options.ssaa = options.get('ssaa', 4)
renderer.pipe.primitive = sample.primitive
elif isinstance(sample, Gaussian):
renderer = GaussianRenderer()
renderer.rendering_options.resolution = options.get('resolution', 512)
renderer.rendering_options.near = options.get('near', 0.8)
renderer.rendering_options.far = options.get('far', 1.6)
renderer.rendering_options.bg_color = options.get('bg_color', (0, 0, 0))
renderer.rendering_options.ssaa = options.get('ssaa', 1)
renderer.pipe.kernel_size = kwargs.get('kernel_size', 0.1)
renderer.pipe.use_mip_gaussian = True
elif isinstance(sample, MeshExtractResult):
renderer = MeshRenderer()
renderer.rendering_options.resolution = options.get('resolution', 512)
renderer.rendering_options.near = options.get('near', 1)
renderer.rendering_options.far = options.get('far', 100)
renderer.rendering_options.ssaa = options.get('ssaa', 4)
else:
raise ValueError(f'Unsupported sample type: {type(sample)}')
rets = {}
for j, (extr, intr) in tqdm(enumerate(zip(extrinsics, intrinsics)), desc='Rendering', disable=not verbose):
if not isinstance(sample, MeshExtractResult):
res = renderer.render(sample, extr, intr, colors_overwrite=colors_overwrite)
if 'color' not in rets: rets['color'] = []
if 'depth' not in rets: rets['depth'] = []
rets['color'].append(np.clip(res['color'].detach().cpu().numpy().transpose(1, 2, 0) * 255, 0, 255).astype(np.uint8))
if 'percent_depth' in res:
rets['depth'].append(res['percent_depth'].detach().cpu().numpy())
elif 'depth' in res:
rets['depth'].append(res['depth'].detach().cpu().numpy())
else:
rets['depth'].append(None)
else:
res = renderer.render(sample, extr, intr)
if 'normal' not in rets: rets['normal'] = []
rets['normal'].append(np.clip(res['normal'].detach().cpu().numpy().transpose(1, 2, 0) * 255, 0, 255).astype(np.uint8))
return rets
def render_video(sample, resolution=512, bg_color=(0, 0, 0), num_frames=300, r=2, fov=40, **kwargs):
yaws = torch.linspace(0, 2 * 3.1415, num_frames)
pitch = 0.25 + 0.5 * torch.sin(torch.linspace(0, 2 * 3.1415, num_frames))
yaws = yaws.tolist()
pitch = pitch.tolist()
extrinsics, intrinsics = yaw_pitch_r_fov_to_extrinsics_intrinsics(yaws, pitch, r, fov)
return render_frames(sample, extrinsics, intrinsics, {'resolution': resolution, 'bg_color': bg_color}, **kwargs)
def render_multiview(sample, resolution=512, nviews=30):
r = 2
fov = 40
cams = [sphere_hammersley_sequence(i, nviews) for i in range(nviews)]
yaws = [cam[0] for cam in cams]
pitchs = [cam[1] for cam in cams]
extrinsics, intrinsics = yaw_pitch_r_fov_to_extrinsics_intrinsics(yaws, pitchs, r, fov)
res = render_frames(sample, extrinsics, intrinsics, {'resolution': resolution, 'bg_color': (0, 0, 0)})
return res['color'], extrinsics, intrinsics
def render_snapshot(samples, resolution=512, bg_color=(0, 0, 0), offset=(-16 / 180 * np.pi, 20 / 180 * np.pi), r=10, fov=8, **kwargs):
yaw = [0, np.pi/2, np.pi, 3*np.pi/2]
yaw_offset = offset[0]
yaw = [y + yaw_offset for y in yaw]
pitch = [offset[1] for _ in range(4)]
extrinsics, intrinsics = yaw_pitch_r_fov_to_extrinsics_intrinsics(yaw, pitch, r, fov)
return render_frames(samples, extrinsics, intrinsics, {'resolution': resolution, 'bg_color': bg_color}, **kwargs)
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