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0d1388f a2f3bcf 0d1388f a2f3bcf 0d1388f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 | import torch
import numpy as np
from tqdm import tqdm
import utils3d
from PIL import Image
import trimesh
from easydict import EasyDict as edict
from typing import List, Tuple
from ..renderers import GaussianRenderer
from ..representations import Octree, Gaussian, MeshExtractResult
from ..modules import sparse as sp
from .random_utils import sphere_hammersley_sequence
from . import postprocessing_utils
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 generate_cameras_spiral(num_views: int, r=2, fov=40) -> Tuple[List[torch.Tensor], List[torch.Tensor]]:
"""生成yaw和pitch的螺旋序列"""
yaws = torch.linspace(0, 2 * np.pi, num_views)
pitchs = 0.25 + 0.5 * torch.sin(torch.linspace(0, 2 * np.pi, num_views))
yaws = yaws.tolist()
pitchs = pitchs.tolist()
extrinsics, intrinsics = yaw_pitch_r_fov_to_extrinsics_intrinsics(yaws, pitchs, r, fov)
return extrinsics, intrinsics
def get_renderer(**kwargs):
renderer = GaussianRenderer()
renderer.rendering_options.resolution = kwargs.get('resolution', 512)
renderer.rendering_options.near = kwargs.get('near', 1)
renderer.rendering_options.far = kwargs.get('far', 3)
renderer.rendering_options.bg_color = kwargs.get('bg_color', (1, 1, 1))
renderer.rendering_options.ssaa = kwargs.get('ssaa', 1)
return renderer
def render_frames(rep_renderer, h, reg_feats, hdri_cond, extrinsics, intrinsics, options={}, colors_overwrite=None, verbose=True, neural_basis=None, tone_mapper=None, return_brm=False, **kwargs):
renderer = get_renderer(**options)
rets = {}
for j, (extr, intr) in tqdm(enumerate(zip(extrinsics, intrinsics)), desc='Rendering', total=len(extrinsics), disable=not verbose):
rep = rep_renderer(h, reg_feats, hdri_cond, extr[None])
res = renderer.render(rep[0], extr, intr, colors_overwrite=colors_overwrite, opt=edict(neural_basis=neural_basis))
if 'color' not in rets: rets['color'] = []
if 'base_color' not in rets: rets['base_color'] = []
if 'roughness' not in rets: rets['roughness'] = []
if 'metallic' not in rets: rets['metallic'] = []
if 'shadow' not in rets: rets['shadow'] = []
if 'alpha' not in rets: rets['alpha'] = []
if 'brm' not in rets: rets['brm'] = []
alpha = res['alpha_view'].detach().cpu().numpy().transpose(1, 2, 0) # 512 512 1
base_color = res['base_color'].detach().cpu().numpy().transpose(1, 2, 0) # 512 512 3
roughness = res['roughness'].detach().cpu().numpy().transpose(1, 2, 0) # 512 512 1
metallic = res['metallic'].detach().cpu().numpy().transpose(1, 2, 0) # 512 512 1
shadow = res['shadow'].detach().cpu().numpy().transpose(1, 2, 0) # 512 512 1
color = res['color'].detach().cpu().numpy().transpose(1, 2, 0) # 512 512 3
color = tone_mapper.hdr_to_ldr(color) # 512 512 3
rets['alpha'].append((alpha * 255).astype(np.uint8))
rets['base_color'].append(((base_color * alpha + (1 - alpha) * options['bg_color'])*255).astype(np.uint8))
if return_brm:
rets['brm'].append(((np.concatenate([np.zeros_like(roughness), roughness, metallic], axis=-1) * alpha)*255).astype(np.uint8))
continue
else:
rets['color'].append(((color * alpha + (1 - alpha) * options['bg_color'])*255).astype(np.uint8))
rets['roughness'].append(((roughness * alpha + (1 - alpha) * options['bg_color'][:1])*255).astype(np.uint8))
rets['metallic'].append(((metallic * alpha + (1 - alpha) * options['bg_color'][:1])*255).astype(np.uint8))
rets['shadow'].append(((shadow * alpha + (1 - alpha) * options['bg_color'])*255).astype(np.uint8))
return edict(rets)
def render_video(render_gs, h, reg_feats, hdri_cond, neural_basis, tone_mapper, resolution=512, bg_color=(1, 1, 1), num_frames=300, r=2, fov=40, **kwargs):
extrinsics, intrinsics = generate_cameras_spiral(num_frames, r, fov)
return render_frames(render_gs, h, reg_feats, hdri_cond, extrinsics, intrinsics, {'resolution': resolution, 'bg_color': bg_color}, neural_basis=neural_basis, tone_mapper=tone_mapper, **kwargs)
def render_single_view(render_gs, h, reg_feats, hdri_cond, neural_basis, tone_mapper, yaw, pitch, r=2, fov=40, resolution=512, bg_color=(1, 1, 1), **kwargs):
extrinsics, intrinsics = yaw_pitch_r_fov_to_extrinsics_intrinsics([yaw], [pitch], r, fov)
return render_frames(render_gs, h, reg_feats, hdri_cond, extrinsics, intrinsics, {'resolution': resolution, 'bg_color': bg_color}, neural_basis=neural_basis, tone_mapper=tone_mapper, **kwargs)
def render_multiview(render_gs, h, reg_feats, hdri_cond, neural_basis, tone_mapper, resolution=512, bg_color=(0, 0, 0), nviews=30, r=2, fov=40, return_brm=True):
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)
rets = render_frames(render_gs, h, reg_feats, hdri_cond, extrinsics, intrinsics, {'resolution': resolution, 'bg_color': bg_color}, neural_basis=neural_basis, tone_mapper=tone_mapper, return_brm=return_brm)
obs = {
'alpha': rets['alpha'],
'base_color': rets['base_color'],
'brm': rets['brm']
}
return edict(obs), extrinsics, intrinsics
def to_glb(
renderer,
h,
reg_feats,
hdri_cond,
neural_basis,
mesh,
tone_mapper,
simplify: float = 0.95,
fill_holes: bool = True,
fill_holes_max_size: float = 0.04,
texture_size: int = 1024,
debug: bool = False,
verbose: bool = False,
) -> trimesh.Trimesh:
if isinstance(mesh, trimesh.Trimesh):
vertices = mesh.vertices
faces = mesh.faces
else:
vertices = mesh.vertices.cpu().detach().numpy()
faces = mesh.faces.cpu().detach().numpy()
# mesh postprocess
vertices, faces = postprocessing_utils.postprocess_mesh(
vertices, faces,
simplify=simplify > 0,
simplify_ratio=simplify,
fill_holes=fill_holes,
fill_holes_max_hole_size=fill_holes_max_size,
fill_holes_max_hole_nbe=int(250 * np.sqrt(1-simplify)),
fill_holes_resolution=512,
fill_holes_num_views=100,
debug=debug,
verbose=verbose,
)
vertices, faces, uvs = postprocessing_utils.parametrize_mesh(vertices, faces)
with torch.inference_mode():
observations, extrinsics, intrinsics = render_multiview(renderer, h, reg_feats, hdri_cond, neural_basis, tone_mapper, resolution=1024, nviews=30)
masks = [np.any(obs_alpha > 0, axis=-1) for obs_alpha in observations['alpha']]
extrinsics = [extrinsics[i].cpu().numpy() for i in range(len(extrinsics))]
intrinsics = [intrinsics[i].cpu().numpy() for i in range(len(intrinsics))]
base_color_texture = postprocessing_utils.bake_texture(
vertices, faces, uvs,
observations['base_color'], masks, extrinsics, intrinsics,
texture_size=texture_size, mode='opt',
lambda_tv=0.01,
verbose=verbose
)
brm_texture = postprocessing_utils.bake_texture(
vertices, faces, uvs,
observations['brm'], masks, extrinsics, intrinsics,
texture_size=texture_size, mode='opt',
lambda_tv=0.01,
verbose=verbose
)
base_color_texture = Image.fromarray(base_color_texture)
brm_texture = Image.fromarray(brm_texture)
# Create material with proper trimesh API
material = trimesh.visual.material.PBRMaterial(
baseColorTexture=base_color_texture,
metallicRoughnessTexture=brm_texture,
)
# Create mesh with texture visuals
visual = trimesh.visual.TextureVisuals(uv=uvs, material=material)
mesh = trimesh.Trimesh(vertices=vertices, faces=faces, visual=visual)
return mesh |