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Functions237 in github.com/chih-hao-lin/urbanir

⨍ Functions 237◇ Types & classes 27
↓ 1 callersMethodread_shadow
(self, dir_shadow, frame_id)
datasets/waymo.py:176
↓ 1 callersFunctionrender_for_test
(hparams, split='test')
render_static.py:36
↓ 1 callersFunctionrsqrtf
models/csrc/include/helper_math.h:78
↓ 1 callersMethodsample_mean
(self, pose)
utils.py:145
↓ 1 callersMethodsample_nearest
(self, pose)
utils.py:135
↓ 1 callersMethodsample_uniform_and_occupied_cells
Sample both M uniform and occupied cells (per cascade) occupied cells are sample from cells with density > @density_threshold
models/networks.py:284
↓ 1 callersFunctionsave_pgm
(result, out_file)
mmseg/run.py:9
↓ 1 callersMethodsetup_poses
(self, cam2world, frame_id)
datasets/waymo.py:87
↓ 1 callersMethodsetup_poses
(self, cam2world_0, cam2world_1, test_id_normalized)
datasets/kitti360.py:109
↓ 1 callersFunctionsph_harm_coeff
Compute spherical harmonic coefficients.
models/ref_util.py:44
↓ 1 callersFunctionspheric_pose
(theta, phi, radius)
datasets/ray_utils.py:193
↓ 1 callersFunctionspherical2vec
(spherical)
render_static.py:28
↓ 1 callersFunctionsurface_points
(rays_o, rays_d, depth)
models/shading.py:36
↓ 1 callersFunctiontest
()
utils.py:155
↓ 1 callersFunctiontest
()
models/volume_render.py:96
↓ 1 callersFunctiontest_NGP
()
models/networks.py:411
↓ 1 callersFunctiontriangulate
()
datasets/tnt.py:329
↓ 1 callersMethodupdate_density_grid
(self, density_threshold, warmup=False, decay=0.95, erode=False)
models/networks.py:361
↓ 1 callersMethodval_in_train
(self)
train.py:287
↓ 1 callersFunctionvec2spherical
(vec)
render_static.py:20
↓ 1 callersFunctionviewmatrix
Construct lookat view matrix.
datasets/ray_utils.py:221
FunctionPYBIND11_MODULE
models/csrc/binding.cpp:458
Method__getitem__
(self, idx)
datasets/base.py:22
Method__init__
(self, hparams)
train.py:58
Method__init__
(self, embed_a_len, poses, ckpt_path=None)
utils.py:106
Method__init__
(self, max, min, k)
losses.py:64
Method__init__
(self, root_dir, split='train', downsample=1.0)
datasets/base.py:9
Method__init__
(self, root_dir, split='train', downsample=1.0, cam_scale_factor=0.95, render_train=False, **kwargs)
datasets/tnt.py:20
Method__init__
(self, root_dir, split='train', downsample=1.0, **kwargs)
datasets/colmap.py:48
Method__init__
(self, root_dir, split, nvs=False, downsample=1.0, load_2d=True, generate_render_path=False, **kwargs)
datasets/waymo.py:18
Method__init__
(self, root_dir, split, nvs=False, downsample=1.0, load_2d=True, generate_render_path=False, **kwargs)
datasets/kitti360.py:16
Method__init__
(self, latent=32, W=128)
models/implicit_mask.py:7
Method__init__
(self)
models/shading.py:41
Method__init__
( self, config, device )
models/shading.py:75
Method__init__
( self, config )
models/shading.py:128
Method__init__
(self, scale, rgb_act='Sigmoid', embed_a=False, embed_a_len=12, classes=7)
models/networks.py:14
Method__len__
(self)
datasets/base.py:17
Function__render_rays_test
Input: rays_o: [h*w, 3] rays origin rays_d: [h*w, 3] rays direction Render rays by while (a ray hasn't converged)
models/rendering.py:47
Function__render_rays_train
Render rays by 1. March the rays along their directions, querying @density_bitfield to skip empty space, and get the effective sample
models/rendering.py:100
Methodadd_flares
(self, rgb, **kwargs)
models/shading.py:121
Functionadd_text
()
utility/video.py:67
Methodbackward
(ctx, dL_dloss)
losses.py:57
Methodbackward
(ctx, dL_drays_a, dL_dxyzs, dL_ddirs, dL_ddeltas, dL_dts, dL_dtotal_samples)
models/custom_functions.py:106
Methodbackward
(ctx, dL_dtotal_samples, dL_dopacity, dL_ddepth, dL_drgb, dL_dalbedo, dL_dnormal_pred, dL_dsem, dL_dvis, dL_dw
models/custom_functions.py:152
Methodbackward
(ctx, dL_dvisibility, dL_dws)
models/custom_functions.py:196
Methodbackward
(ctx, dL_dloss_o, dL_dloss_p)
models/custom_functions.py:219
Methodbackward
(ctx, dL_dout)
models/custom_functions.py:249
Methodbackward
(ctx, dL_dout)
models/custom_functions.py:265
Methodbackward
(ctx, dL_dout)
models/custom_functions.py:281
Functioncenter_poses
See https://github.com/bmild/nerf/issues/34 Inputs: poses: (N_images, 3, 4) pts3d: (N, 3) reconstructed point cloud Outp
datasets/colmap.py:18
Functioncenter_poses
See https://github.com/bmild/nerf/issues/34 Inputs: poses: (N_images, 3, 4) pts3d: (N, 3) reconstructed point cloud Outp
datasets/ray_utils.py:154
Functioncheck_tensor
(tensor, name)
models/networks.py:404
Functioncomposite_alpha_fw
models/csrc/binding.cpp:108
Functioncomposite_refloss_bw
models/csrc/binding.cpp:224
Functioncomposite_refloss_fw
///////////////////////////////////////////
models/csrc/binding.cpp:202
Functioncomposite_test_fw
///////////////////////////////////////////
models/csrc/binding.cpp:254
Functioncomposite_train_bw
models/csrc/binding.cpp:149
Functioncomposite_train_fw
models/csrc/binding.cpp:121
Functioncomposite_visibility_test_fw
models/csrc/binding.cpp:326
Functioncomposite_weight_test_fw
models/csrc/binding.cpp:306
Methodconfigure_optimizers
(self)
train.py:187
Functioncross
models/csrc/include/helper_math.h:345
Functiondistortion_loss_bw
models/csrc/binding.cpp:436
Functiondistortion_loss_fw
models/csrc/binding.cpp:421
Functionextract_frames
()
utility/video.py:12
Methodforward
(self, batch, split)
train.py:85
Methodforward
(self, x, mode='index')
utils.py:116
Methodforward
(ctx, ws, deltas, ts, rays_a)
losses.py:50
Methodforward
(self, results, target, **kwargs)
losses.py:100
Methodforward
(self, uvi)
models/implicit_mask.py:36
Methodforward
(self, d)
models/shading.py:68
Methodforward
Inputs: x: (N, 3) xyz in [-scale, scale] d: (N, 3) directions Outputs: sigmas: (N) r
models/networks.py:184
Methodforward
(ctx, rays_o, rays_d, center, half_size, max_hits)
models/custom_functions.py:29
Methodforward
(ctx, rays_o, rays_d, center, radii, max_hits)
models/custom_functions.py:52
Methodforward
(ctx, rays_o, rays_d, hits_t, density_bitfield, cascades, scale, exp_step_factor,
models/custom_functions.py:81
Methodforward
(ctx, sigmas, rgbs, albedos, normals_pred, sems, viss, deltas, ts, rays_a, T_threshold, classes)
models/custom_functions.py:140
Methodforward
(ctx, sigmas, deltas, ts, rays_a, light_dist, T_threshold)
models/custom_functions.py:186
Methodforward
(ctx, sigmas, normals_diff, normals_ori, deltas, ts, rays_a, T_threshold)
models/custom_functions.py:208
Methodforward
(ctx, x)
models/custom_functions.py:243
Methodforward
(ctx, x)
models/custom_functions.py:256
Methodforward
(ctx, x)
models/custom_functions.py:274
Functiongenerate_ide_fn
Generate integrated directional encoding (IDE) function. This function returns a function that computes the integrated directional encoding from
models/ref_util.py:63
Functiongenerate_video
()
utility/video.py:50
MethodgetWeight
(self, Tcur)
losses.py:71
Methodget_mask
(label, mask_ids)
datasets/kitti360.py:175
Methodget_progress_bar_dict
(self)
train.py:377
Methodget_value
(key)
models/global_var.py:17
Functionguided_filter
Input: image_p: input (h, w) image_i: guided (h, w) r: radius of filter window eps: regularization weight, higher
utils.py:61
Functionintegrated_dir_enc_fn
Function returning integrated directional encoding (IDE). Args: xyz: [..., 3] array of Cartesian coordinates of directions to evaluate at.
models/ref_util.py:94
Functionlength
models/csrc/include/helper_math.h:315
Functionlinear_to_srgb
(img)
datasets/color_utils.py:12
Methodmark_invisible_cells
mark the cells that aren't covered by the cameras with density -1 only executed once before training starts Inputs:
models/networks.py:318
Methodmask_regularize
(self, mask, size_delta, digit_delta)
losses.py:182
Functionmorton3D
models/csrc/binding.cpp:46
Functionmorton3D_invert
models/csrc/binding.cpp:53
Functionnormalize
models/csrc/include/helper_math.h:324
Methodon_validation_start
(self)
train.py:330
Functionoperator*
models/csrc/include/helper_math.h:180
Functionoperator*=
models/csrc/include/helper_math.h:184
Functionoperator+
models/csrc/include/helper_math.h:122
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