Functions — github.com/cvg/NoPoSplat

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Functions553 in github.com/cvg/NoPoSplat

⨍ Functions 553◇ Types & classes 135↳ Endpoints 1

Methodpatch_size

(self)

src/model/encoder/backbone/backbone_croco.py:276

Methodpatch_size

(self)

src/model/encoder/backbone/backbone_dino.py:74

Methodpatch_size

(self)

src/model/encoder/backbone/backbone_croco_multiview.py:230

Methodprint_metrics

(runing_metric, methods=None)

src/model/model_wrapper.py:656

Methodprint_metrics

(runing_metric)

src/evaluation/metric_computer.py:141

Methodprint_metrics

(runing_metric)

src/evaluation/pose_evaluator.py:230

Functionproject

( points: Float[Tensor, "*#batch dim"], extrinsics: Float[Tensor, "*#batch dim+1 dim+1"], intrinsi

src/geometry/projection.py:59

Functionrearrange_head

(feat, patch_size, H, W)

src/model/encoder/encoder_noposplat_multi.py:36

Functionrender_video_interpolation

( gaussians: Gaussians, decoder: Decoder, batch: BatchedExample, num_frames: i

src/visualization/video_render.py:62

Functionrender_video_interpolation_exaggerated

( gaussians: Gaussians, decoder: Decoder, batch: BatchedExample, num_frames: i

src/visualization/video_render.py:89

Functionrender_video_wobble

( gaussians: Gaussians, decoder: Decoder, batch: BatchedExample, num_frames: i

src/visualization/video_render.py:31

Functionresample_kernel

(kernel)

src/misc/weight_modify.py:75

Functionresize

( image: Float[Tensor, "channel height width"], shape: Optional[tuple[int, int]] = None, width: Op

src/visualization/layout.py:208

Functionrope_2d

src/model/encoder/backbone/croco/curope/curope.cpp:49

Functionrsh_cart_0

Computes all real spherical harmonics up to degree 0. This is an autogenerated method. See https://github.com/cheind/torch-spherical-harmonic

src/misc/sht.py:11

Functionrsh_cart_1

Computes all real spherical harmonics up to degree 1. This is an autogenerated method. See https://github.com/cheind/torch-spherical-harmonic

src/misc/sht.py:36

Functionrsh_cart_3

Computes all real spherical harmonics up to degree 3. This is an autogenerated method. See https://github.com/cheind/torch-spherical-harmonic

src/misc/sht.py:110

Functionrsh_cart_5

Computes all real spherical harmonics up to degree 5. This is an autogenerated method. See https://github.com/cheind/torch-spherical-harmonic

src/misc/sht.py:228

Functionrsh_cart_6

Computes all real spherical harmonics up to degree 6. This is an autogenerated method. See https://github.com/cheind/torch-spherical-harmonic

src/misc/sht.py:329

Functionrsh_cart_7

Computes all real spherical harmonics up to degree 7. This is an autogenerated method. See https://github.com/cheind/torch-spherical-harmonic

src/misc/sht.py:509

Functionrt2mat

(R, T)

src/misc/cam_utils.py:47

Methodsample

Arbitrarily sample context and target views.

src/dataset/view_sampler/view_sampler_arbitrary.py:22

Methodsample

( self, scene: str, extrinsics: Float[Tensor, "view 4 4"], intrinsics: Float[T

src/dataset/view_sampler/view_sampler_bounded.py:29

Methodsample

( self, scene: str, extrinsics: Float[Tensor, "view 4 4"], intrinsics: Float[T

src/dataset/view_sampler/view_sampler_all.py:17

Methodsample

( self, scene: str, extrinsics: Float[Tensor, "view 4 4"], intrinsics: Float[T

src/dataset/view_sampler/view_sampler_evaluation.py:48

Functionsample_discrete_distribution

( pdf: Float[Tensor, "*batch bucket"], num_samples: int, eps: float = torch.finfo(torch.float32).e

src/misc/discrete_probability_distribution.py:7

Functionsample_training_rays

( image: Float[Tensor, "batch view channel ..."], intrinsics: Float[Tensor, "batch view dim dim"],

src/geometry/projection.py:154

Methodsave_index

(self)

src/evaluation/evaluation_index_generator.py:155

Functionseparate_dataset_cfg_wrappers

(joined: dict)

src/config.py:86

Functionseparate_loss_cfg_wrappers

src/model/encoder/backbone/backbone_croco.py:118

Methodset_freeze

(self, freeze)

src/model/encoder/backbone/backbone_croco_multiview.py:109

Methodsetup

(self, croconet)

src/model/encoder/heads/linear_head.py:27

Methodsetup

(self, croconet)

src/model/encoder/heads/linear_head.py:59

Methodshuffle

(self, lst: list)

src/dataset/dataset_scannet_pose.py:78

Methodtest_dataloader

(self)

src/dataset/data_module.py:125

Methodtest_step

(self, batch, batch_idx)

src/model/model_wrapper.py:214

Methodtest_step

(self, batch, batch_idx)

src/evaluation/evaluation_index_generator.py:49

Methodtest_step

(self, batch, batch_idx)

src/evaluation/metric_computer.py:29

Methodtest_step

(self, batch, batch_idx)

src/evaluation/pose_evaluator.py:48

Methodtrain_dataloader

(self)

src/dataset/data_module.py:90

Methodtraining_step

(self, batch, batch_idx)

src/model/model_wrapper.py:133

Methodtrajectory_fn

(t)

src/model/model_wrapper.py:484

Methodunpatchify

x: (N, L, patch_size**2 *channels) imgs: (N, 3, H, W)

src/model/encoder/backbone/croco/croco.py:218

Methodval_dataloader

(self)

src/dataset/data_module.py:108

Methodvalidation_step

(self, batch, batch_idx, dataloader_idx=0)

src/model/model_wrapper.py:366

Methodversion

(self)

src/misc/LocalLogger.py:23

Methodvisualize

( self, context: BatchedViews, global_step: int, )

src/model/encoder/visualization/encoder_visualizer_epipolar.py:34

Methodvisualize_attention

( self, context_images: Float[Tensor, "batch view 3 height width"], sampling: Epipolar

src/model/encoder/visualization/encoder_visualizer_epipolar.py:128

Methodvisualize_probabilities

( self, context_images: Float[Tensor, "batch view 3 height width"], sampling: Epipolar

src/model/encoder/visualization/encoder_visualizer_epipolar.py:300

Functionworker_init_fn

(worker_id: int)

src/dataset/data_module.py:53

Functionwrapper_no

(decout, true_shape, ray_embedding=None)

src/model/encoder/backbone/croco/misc.py:76

Functionwrapper_yes

(decout, true_shape, ray_embedding=None)

src/model/encoder/backbone/croco/misc.py:83

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