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Functions605 in github.com/cuiziteng/Aleth-NeRF

⨍ Functions 605◇ Types & classes 78

↓ 1 callersFunctionsimilarity_from_cameras

Get a similarity transform to normalize dataset from c2w (OpenCV convention) cameras :param c2w: (N, 4) :return T (4,4) , scale (floa

src/data/data_util/tnt.py:31

↓ 1 callersFunctionsimilarity_from_cameras

Get a similarity transform to normalize dataset from c2w (OpenCV convention) cameras :param c2w: (N, 4) :return T (4,4) , scale (floa

src/data/data_util/nerf_360_v2.py:279

↓ 1 callersFunctionsimilarity_from_cameras

Get a similarity transform to normalize dataset from c2w (OpenCV convention) cameras :param c2w: (N, 4) :return T (4,4) , scale (floa

src/data/data_util/refnerf_real.py:277

↓ 1 callersFunctionsimilarity_from_cameras

Get a similarity transform to normalize dataset from c2w (OpenCV convention) cameras :param c2w: (N, 4) :return T (4,4) , scale (floa

src/data/data_util/lf.py:31

↓ 1 callersFunctionsorted_piecewise_constant_pdf

( bins, weights, num_samples, randomized, float_min_eps=2**-32 )

src/model/nerf/helper.py:101

↓ 1 callersFunctionsorted_piecewise_constant_pdf

( bins, weights, num_samples, randomized, float_min_eps=2**-32 )

src/model/mipnerf/helper.py:88

↓ 1 callersFunctionsorted_piecewise_constant_pdf

( bins, weights, num_samples, randomized, float_min_eps=2**-32 )

src/model/refnerf/helper.py:96

↓ 1 callersFunctionsorted_piecewise_constant_pdf

( bins, weights, num_samples, randomized, float_min_eps=2**-32 )

src/model/nerfpp/helper.py:103

↓ 1 callersFunctionsorted_piecewise_constant_pdf

( bins, weights, num_samples, randomized, float_min_eps=2**-32 )

src/model/aleth_nerf/helper.py:198

↓ 1 callersFunctionsorted_piecewise_constant_pdf

( bins, weights, num_samples, randomized, float_min_eps=2**-32 )

src/model/aleth_nerf_exp/helper.py:220

↓ 1 callersMethodsparsify_background

( self, sigma_thresh: float = 1.0, dilate: int = 1 # BEFORE resampling! )

src/model/plenoxel/sparse_grid.py:662

↓ 1 callersFunctionsph_harm_coeff

Compute spherical harmonic coefficients.

src/model/refnerf/ref_utils.py:89

↓ 1 callersFunctionspherify_poses

src/data/data_util/llff.py:215

↓ 1 callersFunctionspherify_poses

src/data/data_util/llff_single.py:118

↓ 1 callersFunctionspherify_poses

src/data/data_util/llff_pair.py:229

↓ 1 callersMethodstep

(self, closure)

src/model/plenoxel/model.py:29

↓ 1 callersMethodtest_step

(self, batch, batch_idx)

src/model/nerf/model.py:256

↓ 1 callersFunctionto8b_depth

utils/store_image.py:18

↓ 1 callersFunctiontransform_pose_llff

src/data/data_util/nerf_360_v2.py:337

↓ 1 callersFunctiontransform_pose_llff

src/data/data_util/refnerf_real.py:333

↓ 1 callersMethodtv

Compute total variation over sigma, similar to Neural Volumes [Lombardi et al., ToG 2019] :return: torch.Tensor, size scalar

src/model/plenoxel/sparse_grid.py:769

↓ 1 callersFunctionunpad_poses

Remove the homogeneous bottom row from [..., 4, 4] pose matrices.

src/data/pose_utils.py:10

↓ 1 callersMethodupdate_masked_sampler

src/data/interface.py:186

↓ 1 callersMethodupdate_occupancy_cache

src/model/dvgo/dvgo.py:276

↓ 1 callersMethodupdate_occupancy_cache_lt_nviews

( self, rays_o_tr, rays_d_tr, imsz, render_kwargs, maskout_lt_nviews )

src/model/dvgo/dmpigo.py:273

↓ 1 callersFunctionviewmatrix

Construct lookat view matrix.

src/data/pose_utils.py:61

↓ 1 callersMethodvolume_render_depth

Volumetric depth rendering for rays :param rays: Rays, (origins (N, 3), dirs (N, 3)) :param sigma_thresh: finds the first po

src/model/plenoxel/sparse_grid.py:435

↓ 1 callersMethodvoxel_count_views

( self, rays_o_tr, rays_d_tr, imsz, near, far, stepsiz

src/model/dvgo/dvgo.py:298

↓ 1 callersMethodworld2grid

World coordinates to grid coordinates. Grid coordinates are normalized to [0, n_voxels] in each side :param points: (N, 3)

src/model/plenoxel/sparse_grid.py:739

FunctionL1_loss

src/model/aleth_nerf/helper.py:50

FunctionL1_loss

src/model/aleth_nerf_exp/helper.py:50

FunctionPYBIND11_MODULE

lib/plenoxel/svox2.cpp:50

FunctionPYBIND11_MODULE

lib/dvgo/render_utils.cpp:170

FunctionPYBIND11_MODULE

lib/dvgo/ub360_utils.cpp:20

FunctionPYBIND11_MODULE

lib/dvgo/adam_upd.cpp:79

FunctionPYBIND11_MODULE

lib/dvgo/total_variation.cpp:22

FunctionPYBIND11_MODULE

lib/dvgo/cuda/render_utils.cpp:170

FunctionPYBIND11_MODULE

lib/dvgo/cuda/ub360_utils.cpp:20

FunctionPYBIND11_MODULE

lib/dvgo/cuda/adam_upd.cpp:79

FunctionPYBIND11_MODULE

lib/dvgo/cuda/total_variation.cpp:22

FunctionSmooth_loss

src/model/aleth_nerf/helper.py:41

FunctionSmooth_loss

src/model/aleth_nerf_exp/helper.py:41

Method__enter__

src/model/plenoxel/utils.py:576

(self, type, value, traceback)

src/model/plenoxel/utils.py:581

Method__getitem__

src/model/plenoxel/dataclass.py:85

Method__getitem__

src/data/interface.py:336

( self, min_deg_point, max_deg_point, deg_view, netdepth: int = 8,

src/model/nerf/model.py:29

( self, lr_init: float = 5.0e-4, lr_final: float = 5.0e-6, lr_delay_steps: int

src/model/nerf/model.py:197

( self, min_deg_point, max_deg_point, deg_view, netdepth: int = 8,

src/model/mipnerf/model.py:26

( self, lr_init: float = 5.0e-4, lr_final: float = 5.0e-6, lr_delay_steps: int

src/model/mipnerf/model.py:198

( self, size: torch.Tensor, rorigins: torch.Tensor, rdirs: torch.Tensor,

src/model/plenoxel/utils.py:393

src/model/plenoxel/utils.py:573

( self, reso: Union[int, List[int], Tuple[int, int, int]] = 128, radius: Union[float,

src/model/plenoxel/sparse_grid.py:34

( self, backend: str = "cuvol", background_brightness: float = 1.0, step_size:

src/model/plenoxel/dataclass.py:35

(self, upsamp_every)

src/model/plenoxel/model.py:40

( self, reso: List[List[int]] = [[256, 256, 256], [512, 512, 512]], upsample_step: Lis

src/model/plenoxel/model.py:91

( self, deg_view, min_deg_point: int = 0, max_deg_point: int = 16, net

src/model/refnerf/model.py:29

( self, lr_init: float = 5.0e-4, lr_final: float = 5.0e-6, lr_delay_steps: int

src/model/refnerf/model.py:297

( self, min_deg_point, max_deg_point, deg_view, netdepth: int = 8,

src/model/nerfpp/model.py:27

( self, lr_init: float = 5.0e-4, lr_final: float = 5.0e-6, lr_delay_steps: int

src/model/nerfpp/model.py:244

( self, K_g: float = 0.5, # Initial Global Density Value num_levels: int = 2,

src/model/aleth_nerf/model.py:141

( self, eta: float = 0.4, # Enhance Lightness Degree (0.35~0.55 all OK) con: f

src/model/aleth_nerf/model.py:262

(self, contrast)

src/model/aleth_nerf/helper.py:54

(self, mean_val=0.5)

src/model/aleth_nerf/helper.py:94

( self, K_g: float = 1.0, # Initial Global Density Value num_levels: int = 2,

src/model/aleth_nerf_exp/model.py:141

( self, mode: str = 'overexp', # 'dark' or 'overexp' condition eta: float = 0.5,

src/model/aleth_nerf_exp/model.py:260

(self, contrast)

src/model/aleth_nerf_exp/helper.py:54

(self, mean_val=0.5)

src/model/aleth_nerf_exp/helper.py:94

(self, params, lr=1e-3, betas=(0.9, 0.99), eps=1e-8)

src/model/dvgo/masked_adam.py:22

( self, xyz_min, xyz_max, num_voxels=0, num_voxels_base=0, alp

src/model/dvgo/dcvgo.py:28

(self, channels, world_size, xyz_min, xyz_max, **kwargs)

src/model/dvgo/grid.py:37

(self, channels, world_size, xyz_min, xyz_max, config)

src/model/dvgo/grid.py:103

( self, xyz_min, xyz_max, num_voxels=0, num_voxels_base=0, alp

src/model/dvgo/dvgo.py:25

( self, xyz_min, xyz_max, num_voxels=0, mpi_depth=0, mask_cach

src/model/dvgo/dmpigo.py:29

( self, model_type: str = "dvgo", ray_masking: bool = False, bbox_type="bounde

src/model/dvgo/model.py:159

( self, datadir: str, scene_name: str, # LLFF specific arguments llffh

src/data/litdata.py:27

( self, datadir: str, scene_name: str, # LLFF specific arguments facto

src/data/litdata.py:78

( self, datadir: str, scene_name: str, # LLFF specific arguments facto

src/data/litdata.py:131

( self, datadir: str, scene_name: str, # Compare method compare_method

src/data/litdata.py:184

( self, datadir: str, scene_name: str, # TnT specific cam_scale_factor

src/data/litdata.py:225

( self, datadir: str, scene_name: str, # Blender specific train_skip:

src/data/litdata.py:303

( self, datadir: str, scene_name: str, factor: int = 4, cam_scale_fact

src/data/litdata.py:342

( self, datadir: str, scene_name: str, # ShinyBlender specific train_s

src/data/litdata.py:383

( self, datadir: str, scene_name: str, factor: int = 4, cam_scale_fact

src/data/litdata.py:422

( self, datadir: str, batch_size: int = 4096, chunk: int = 1024 * 32,

src/data/interface.py:27

(self, batch_size, num_replicas, rank, N_total, tpu)

src/data/sampler.py:36

( self, batch_size, num_replicas, rank, N_img, N_pixels,

src/data/sampler.py:49

( self, batch_size, num_replicas, rank, N_img, N_pixels,

src/data/sampler.py:129

(self, batch_size, num_replicas, rank, total_len, epoch_size, tpu)

src/data/sampler.py:182

( self, batch_size, num_replicas, rank, total_len, N_img,

src/data/sampler.py:206

src/model/dvgo/grid.py:89

src/data/sampler.py:40

src/data/sampler.py:68

src/data/sampler.py:148

src/data/sampler.py:189

src/data/sampler.py:227

src/data/interface.py:360

src/data/sampler.py:44

src/data/sampler.py:124

src/data/sampler.py:177

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