GitLab

* add pre-computed transmittance_

* add prefix_trans to all render  functions

* Fixed traversal with far_plane

* test added for traversal with near and far planes

* More correct test

* black formatting for test

* Per-ray min-max distances in sampling

* Test for sampling with min/max distances added

* black formatting

* Fixed traversal with far_plane

* test added for traversal with near and far planes

* More correct test

* black formatting for test

* opencv_lens_undistortion

* fix k4 bug for undistortion, support fisheye

* support k3 k4 k5 k6

* fix _opencv_len_distortion; format

* naming: len->lens

* update workflow; fix Literal

* fix format

* fix typo

* fix workflow for cu102

* update workflow; fix Literal

* fix format

* fix typo

* update workflow; fix Literal

* fix format

* update workflow

* tiny fix

* format

* format

* fix workflow

* fix workflow

* update cuda env file

* update workflow

* tiny fix

* format

* format

* fix workflow

* fix workflow

* update workflow

* tiny fix

* format

* format

* fix workflow

* update workflow

* tiny fix

* format

* format

* missing docs for the 4 dropin examples

* fix docs

* profiling in coding.rst

update the doc

* importance_sampling with test

* package importance_sampling

* compute_intervals tested and packaged

* compute_intervals_v2

* bicycle is failing

* fix cut in compute_intervals_v2, test pass for rendering

* hacky way to get opaque_bkgd work

* reorg ING

* PackedRaySegmentsSpec

* chunk_ids -> ray_ids

* binary -> occupied

* test_traverse_grid_basic checked

* fix traverse_grid with step size, checked

* support max_step_size, not verified

* _cuda and cuda; upgrade ray_marching

* inclusive scan

* test_exclusive_sum but seems to have numeric error

* inclusive_sum_backward verified

* exclusive sum backward

* merge fwd and bwd for scan

* inclusive & exclusive prod verified

* support normal scan with torch funcs

* rendering and tests

* a bit clean up

* importance_sampling verified

* stratified for importance_sampling

* importance_sampling in pdf.py

* RaySegmentsSpec in data_specs; fix various bugs

* verified with _proposal_packed.py

* importance sampling support batch input/output. need to verify

* prop script with batch samples

* try to use cumsum  instead of cumprod

* searchsorted

* benchmarking prop

* ray_aabb_intersect untested

* update prop benchmark numbers

* minor fixes

* batched ray_aabb_intersect

* ray_aabb_intersect and traverse with grid(s)

* tiny optimize for traverse_grids kernels

* traverse_grids return intervals and samples

* cub not verified

* cleanup

* propnet and occgrid as estimators

* training print iters 10k

* prop is good now

* benchmark in google sheet.

* really cleanup: scan.py and test

* pack.py and test

* rendering and test

* data_specs.py and pdf.py docs

* data_specs.py and pdf.py docs

* init and headers

* grid.py and test for it

* occ grid docs

* generated docs

* example docs for pack and scan function.

* doc fix for volrend.py

* doc fix for pdf.py

* fix doc for rendering function

* docs

* propnet docs

* update scripts

* docs: index.rst

* methodology docs

* docs for examples

* mlp nerf script

* update t-nerf script

* rename dnerf to tnerf

* misc update

* bug fix: pdf_loss with test

* minor fix

* update readme with submodules

* fix format

* update gitingore file

* fix doc failure. teaser png to jpg

* docs in examples/

* Fix train_mlp_nerf

* Fix black and isort

* multres grid

* prop

* benchmark with prop and occ

* benchmark blender with weight_decay

* docs

* bump version

* move torch data transfer into dataloader

* Update README

* use args.data_root

* Remove redundant check

* Fix isort

* Fix black

* Fix the link to train_mlp_nerf

* Fix the link