Commits · 4233c32887a28d09634768586014bf6fd705f6f1 · OpenDAS / pytorch3d

24 Feb, 2020 3 commits

cpu wheel builds for linux and mac · 4233c328

Jeremy Reizenstein authored Feb 24, 2020

Reviewed By: nikhilaravi

Differential Revision: D20073426

fbshipit-source-id: fce83c9b63d630de1e6ebe2ff4790f29d11b65cc

4233c328

Update bundle_adjustment.ipynb (#81) · 40be4cf7

Tyler Barron authored Feb 24, 2020

Summary:
*: Fixed references to colors in the diagram
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/81

Reviewed By: bottler

Differential Revision: D20064048

Pulled By: nikhilaravi

fbshipit-source-id: a70ee446f1223ec900072a2380c75ed95fb4431d

40be4cf7

CI updates · dab7f61a

Jeremy Reizenstein authored Feb 24, 2020

Summary: Document existence of nightly build. Fix some mistakes in windows-related CI code (not running yet).

Reviewed By: nikhilaravi

Differential Revision: D20030293

fbshipit-source-id: 2199ea7c6d34e881aa5641726feb6bfc20337ce3

dab7f61a

21 Feb, 2020 3 commits

fix docstring of mesh edge loss · c2a0a3e3

Georgia Gkioxari authored Feb 21, 2020

Summary: Fix docstring for mesh edge loss

Reviewed By: jcjohnson

Differential Revision: D20040560

fbshipit-source-id: 01a3ee9473c7d11583684bf4cd200caa1d3f0260

c2a0a3e3

lint things · e491efb8

Jeremy Reizenstein authored Feb 21, 2020

Summary:
Lint related fixes: Improve internal/OSS consistency. Fix the fight between black and certain pyre-ignore markers by moving them to the line before.
Use clang-format-8 automatically if present. Small number of pyre fixes.

arc doesn't run pyre at the moment, so I put back the explicit call to pyre. I don't know if there's an option somewhere to change this.

Reviewed By: nikhilaravi

Differential Revision: D19780518

fbshipit-source-id: ef1c243392322fa074130f6cff2dd8a6f7738a7f

e491efb8

Fixed windows MSVC build compatibility (#9) · 9e21659f

merayxu authored Feb 20, 2020

Summary:
Fixed a few MSVC compiler (visual studio 2019, MSVC 19.16.27034) compatibility issues
1. Replaced long with int64_t. aten::data_ptr\<long\> is not supported in MSVC
2. pytorch3d/csrc/rasterize_points/rasterize_points_cpu.cpp, inline function is not correctly recognized by MSVC.
3. pytorch3d/csrc/rasterize_meshes/geometry_utils.cuh
const auto kEpsilon = 1e-30;
MSVC does not compile this const into both host and device, change to a MACRO.
4. pytorch3d/csrc/rasterize_meshes/geometry_utils.cuh,
const float area2 = pow(area, 2.0);
2.0 is considered as double by MSVC and raised an error
5. pytorch3d/csrc/rasterize_points/rasterize_points_cpu.cpp
std::tuple<torch::Tensor, torch::Tensor> RasterizePointsCoarseCpu() return type does not match the declaration in rasterize_points_cpu.h.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/9

Reviewed By: nikhilaravi

Differential Revision: D19986567

Pulled By: yuanluxu

fbshipit-source-id: f4d98525d088c99c513b85193db6f0fc69c7f017

9e21659f

20 Feb, 2020 3 commits

face areas backward · a3baa367

Georgia Gkioxari authored Feb 20, 2020

Summary:
Added backward for mesh face areas & normals. Exposed it as a layer. Replaced the computation with the new op in Meshes and in Sample Points.

Current issue: Circular imports. I moved the import of the op in meshes inside the function scope.

Reviewed By: jcjohnson

Differential Revision: D19920082

fbshipit-source-id: d213226d5e1d19a0c8452f4d32771d07e8b91c0a

a3baa367

Fix spelling of "Gouraud" · 9ca54891

Patrick Labatut authored Feb 20, 2020

Summary: Fix spelling of *Gouraud* in [Gouraud shading](https://en.wikipedia.org/wiki/Gouraud_shading).

Reviewed By: nikhilaravi

Differential Revision: D19943547

fbshipit-source-id: 5c016b7b051a7b33a7b68ed5303b642d9e834bbd

9ca54891

Shader API more consistent naming · f0dc6511

Nikhila Ravi authored Feb 19, 2020

Summary:
Renamed shaders to be prefixed with Hard/Soft depending on if they use a probabalistic blending (Soft) or use the closest face (Hard).

There is some code duplication but I thought it would be cleaner to have separate shaders for each task rather than:
- inheritance (which we discussed previously that we want to avoid)
- boolean (hard/soft) or a string (hard/soft) - new blending functions other than the ones provided would need if statements in the current shaders which might get messy.

Also added a `flat_shading` function and a `FlatShader` - I could make this into a tutorial as it was really easy to add a new shader and it might be a nice showcase.

NOTE: There are a few more places where the naming will need to change (e.g the tutorials) but I wanted to reach a consensus on this before changing it everywhere.

Reviewed By: jcjohnson

Differential Revision: D19761036

fbshipit-source-id: f972f6530c7f66dc5550b0284c191abc4a7f6fc4

f0dc6511

19 Feb, 2020 3 commits

cpp support for packed to padded · 60f3c4e7

Georgia Gkioxari authored Feb 19, 2020

Summary:
Cpu implementation for packed to padded and added gradients
```
Benchmark                                     Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
PACKED_TO_PADDED_2_100_300_1_cpu                    138             221           3625
PACKED_TO_PADDED_2_100_300_1_cuda:0                 184             261           2716
PACKED_TO_PADDED_2_100_300_16_cpu                   555             726            901
PACKED_TO_PADDED_2_100_300_16_cuda:0                179             260           2794
PACKED_TO_PADDED_2_100_3000_1_cpu                   396             519           1262
PACKED_TO_PADDED_2_100_3000_1_cuda:0                181             274           2764
PACKED_TO_PADDED_2_100_3000_16_cpu                 4517            5003            111
PACKED_TO_PADDED_2_100_3000_16_cuda:0               224             397           2235
PACKED_TO_PADDED_2_1000_300_1_cpu                   138             212           3616
PACKED_TO_PADDED_2_1000_300_1_cuda:0                180             282           2775
PACKED_TO_PADDED_2_1000_300_16_cpu                  565             711            885
PACKED_TO_PADDED_2_1000_300_16_cuda:0               179             264           2797
PACKED_TO_PADDED_2_1000_3000_1_cpu                  389             494           1287
PACKED_TO_PADDED_2_1000_3000_1_cuda:0               180             271           2777
PACKED_TO_PADDED_2_1000_3000_16_cpu                4522            5170            111
PACKED_TO_PADDED_2_1000_3000_16_cuda:0              216             286           2313
PACKED_TO_PADDED_10_100_300_1_cpu                   251             345           1995
PACKED_TO_PADDED_10_100_300_1_cuda:0                178             262           2806
PACKED_TO_PADDED_10_100_300_16_cpu                 2354            2750            213
PACKED_TO_PADDED_10_100_300_16_cuda:0               178             291           2814
PACKED_TO_PADDED_10_100_3000_1_cpu                 1519            1786            330
PACKED_TO_PADDED_10_100_3000_1_cuda:0               179             237           2791
PACKED_TO_PADDED_10_100_3000_16_cpu               24705           25879             21
PACKED_TO_PADDED_10_100_3000_16_cuda:0              228             316           2191
PACKED_TO_PADDED_10_1000_300_1_cpu                  261             432           1919
PACKED_TO_PADDED_10_1000_300_1_cuda:0               181             261           2756
PACKED_TO_PADDED_10_1000_300_16_cpu                2349            2770            213
PACKED_TO_PADDED_10_1000_300_16_cuda:0              180             256           2782
PACKED_TO_PADDED_10_1000_3000_1_cpu                1613            1929            310
PACKED_TO_PADDED_10_1000_3000_1_cuda:0              183             253           2739
PACKED_TO_PADDED_10_1000_3000_16_cpu              22041           23653             23
PACKED_TO_PADDED_10_1000_3000_16_cuda:0             220             343           2270
PACKED_TO_PADDED_32_100_300_1_cpu                   555             750            901
PACKED_TO_PADDED_32_100_300_1_cuda:0                188             282           2661
PACKED_TO_PADDED_32_100_300_16_cpu                 7550            8131             67
PACKED_TO_PADDED_32_100_300_16_cuda:0               181             272           2770
PACKED_TO_PADDED_32_100_3000_1_cpu                 4574            6327            110
PACKED_TO_PADDED_32_100_3000_1_cuda:0               173             254           2884
PACKED_TO_PADDED_32_100_3000_16_cpu               70366           72563              8
PACKED_TO_PADDED_32_100_3000_16_cuda:0              349             654           1433
PACKED_TO_PADDED_32_1000_300_1_cpu                  612             728            818
PACKED_TO_PADDED_32_1000_300_1_cuda:0               189             295           2647
PACKED_TO_PADDED_32_1000_300_16_cpu                7699            8254             65
PACKED_TO_PADDED_32_1000_300_16_cuda:0              189             311           2646
PACKED_TO_PADDED_32_1000_3000_1_cpu                5105            5261             98
PACKED_TO_PADDED_32_1000_3000_1_cuda:0              191             260           2625
PACKED_TO_PADDED_32_1000_3000_16_cpu              87073           92708              6
PACKED_TO_PADDED_32_1000_3000_16_cuda:0             344             425           1455
--------------------------------------------------------------------------------

Benchmark                                           Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
PACKED_TO_PADDED_TORCH_2_100_300_1_cpu                    492             627           1016
PACKED_TO_PADDED_TORCH_2_100_300_1_cuda:0                 768             975            652
PACKED_TO_PADDED_TORCH_2_100_300_16_cpu                   659             804            760
PACKED_TO_PADDED_TORCH_2_100_300_16_cuda:0                781             918            641
PACKED_TO_PADDED_TORCH_2_100_3000_1_cpu                   624             734            802
PACKED_TO_PADDED_TORCH_2_100_3000_1_cuda:0                778             929            643
PACKED_TO_PADDED_TORCH_2_100_3000_16_cpu                 2609            2850            192
PACKED_TO_PADDED_TORCH_2_100_3000_16_cuda:0               758             901            660
PACKED_TO_PADDED_TORCH_2_1000_300_1_cpu                   467             612           1072
PACKED_TO_PADDED_TORCH_2_1000_300_1_cuda:0                772             905            648
PACKED_TO_PADDED_TORCH_2_1000_300_16_cpu                  689             839            726
PACKED_TO_PADDED_TORCH_2_1000_300_16_cuda:0               789            1143            635
PACKED_TO_PADDED_TORCH_2_1000_3000_1_cpu                  629             735            795
PACKED_TO_PADDED_TORCH_2_1000_3000_1_cuda:0               812             916            616
PACKED_TO_PADDED_TORCH_2_1000_3000_16_cpu                2716            3117            185
PACKED_TO_PADDED_TORCH_2_1000_3000_16_cuda:0              844            1288            593
PACKED_TO_PADDED_TORCH_10_100_300_1_cpu                  2387            2557            210
PACKED_TO_PADDED_TORCH_10_100_300_1_cuda:0               4112            4993            122
PACKED_TO_PADDED_TORCH_10_100_300_16_cpu                 3385            4254            148
PACKED_TO_PADDED_TORCH_10_100_300_16_cuda:0              3959            4902            127
PACKED_TO_PADDED_TORCH_10_100_3000_1_cpu                 2918            3105            172
PACKED_TO_PADDED_TORCH_10_100_3000_1_cuda:0              4054            4450            124
PACKED_TO_PADDED_TORCH_10_100_3000_16_cpu               12748           13623             40
PACKED_TO_PADDED_TORCH_10_100_3000_16_cuda:0             4023            4395            125
PACKED_TO_PADDED_TORCH_10_1000_300_1_cpu                 2258            2492            222
PACKED_TO_PADDED_TORCH_10_1000_300_1_cuda:0              3997            4312            126
PACKED_TO_PADDED_TORCH_10_1000_300_16_cpu                3404            3597            147
PACKED_TO_PADDED_TORCH_10_1000_300_16_cuda:0             3877            4227            129
PACKED_TO_PADDED_TORCH_10_1000_3000_1_cpu                2789            3054            180
PACKED_TO_PADDED_TORCH_10_1000_3000_1_cuda:0             3821            4402            131
PACKED_TO_PADDED_TORCH_10_1000_3000_16_cpu              11967           12963             42
PACKED_TO_PADDED_TORCH_10_1000_3000_16_cuda:0            3729            4290            135
PACKED_TO_PADDED_TORCH_32_100_300_1_cpu                  6933            8152             73
PACKED_TO_PADDED_TORCH_32_100_300_1_cuda:0              11856           12287             43
PACKED_TO_PADDED_TORCH_32_100_300_16_cpu                 9895           11205             51
PACKED_TO_PADDED_TORCH_32_100_300_16_cuda:0             12354           13596             41
PACKED_TO_PADDED_TORCH_32_100_3000_1_cpu                 9516           10128             53
PACKED_TO_PADDED_TORCH_32_100_3000_1_cuda:0             12917           13597             39
PACKED_TO_PADDED_TORCH_32_100_3000_16_cpu               41209           43783             13
PACKED_TO_PADDED_TORCH_32_100_3000_16_cuda:0            12210           13288             41
PACKED_TO_PADDED_TORCH_32_1000_300_1_cpu                 7179            7689             70
PACKED_TO_PADDED_TORCH_32_1000_300_1_cuda:0             11896           12381             43
PACKED_TO_PADDED_TORCH_32_1000_300_16_cpu               10127           15494             50
PACKED_TO_PADDED_TORCH_32_1000_300_16_cuda:0            12034           12817             42
PACKED_TO_PADDED_TORCH_32_1000_3000_1_cpu                8743           10251             58
PACKED_TO_PADDED_TORCH_32_1000_3000_1_cuda:0            12023           12908             42
PACKED_TO_PADDED_TORCH_32_1000_3000_16_cpu              39071           41777             13
PACKED_TO_PADDED_TORCH_32_1000_3000_16_cuda:0           11999           13690             42
--------------------------------------------------------------------------------
```

Reviewed By: bottler, nikhilaravi, jcjohnson

Differential Revision: D19870575

fbshipit-source-id: 23a2477b73373c411899633386c87ab034c3702a

60f3c4e7

transforms 3d convention fix · 8301163d

Nikhila Ravi authored Feb 19, 2020

Summary: Fixed the rotation matrices generated by the RotateAxisAngle class and updated the tests. Added documentation for Transforms3d to clarify the conventions.

Reviewed By: gkioxari

Differential Revision: D19912903

fbshipit-source-id: c64926ce4e1381b145811557c32b73663d6d92d1

8301163d

MACOSX_DEPLOYMENT_TARGET=10.14 · bdc2bb57

Jeremy Reizenstein authored Feb 19, 2020

Summary:
pybind now seems to need C++17 on a mac, so advise people to use it. (Also delete an unused variable to silence a warning I got on a mac build.)

Reported in github issue #68.

Reviewed By: nikhilaravi

Differential Revision: D19970512

fbshipit-source-id: f9be20c8ed425bd6ba8d009a7d62dad658dccdb1

bdc2bb57

18 Feb, 2020 2 commits

Update obj_io.py: Make PyTorch3D work with ShapeNetCore.v2 (#49) · 23465890

Chr1k0 authored Feb 18, 2020

Summary:
Making PyTorch3D work with ShapeNetCore.v2 models from http://shapenet.cs.stanford.edu/shapenet/obj-zip/ShapeNetCore.v2/
The face identifier of the ShapeNetCore.v2 models is followed by two not one blank - example:
"f  1/1/1 2/2/2 3/3/3" instead of
"f 1/1/1 2/2/2 3/3/3"
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/49

Differential Revision: D19951828

Pulled By: gkioxari

fbshipit-source-id: 5695df0fca2059e75eeb73edf4cfe9d9f008e841

23465890

Fix typo (#54) · 3ba43980

Junior Rojas authored Feb 18, 2020

Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/54

Differential Revision: D19951851

Pulled By: gkioxari

fbshipit-source-id: cf41d5806c761639d1efa42a633404b248486c30

3ba43980

14 Feb, 2020 1 commit

lint fixes · 97acf16d

Nikhila Ravi authored Feb 13, 2020

Summary: Ran `dev/linter.sh`.

Reviewed By: bottler

Differential Revision: D19761062

fbshipit-source-id: 1a49abe4a5f2bc7641b2b46e254aa77e6a48aa7d

97acf16d

13 Feb, 2020 2 commits

CPU implem for face areas normals · 29cd181a

Georgia Gkioxari authored Feb 13, 2020

Summary:
Added cpu implementation for face areas normals. Moved test and bm to separate functions.

```
Benchmark                                   Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
FACE_AREAS_NORMALS_2_100_300_False                196             268           2550
FACE_AREAS_NORMALS_2_100_300_True                 106             179           4733
FACE_AREAS_NORMALS_2_100_3000_False              1447            1630            346
FACE_AREAS_NORMALS_2_100_3000_True                107             178           4674
FACE_AREAS_NORMALS_2_1000_300_False               201             309           2486
FACE_AREAS_NORMALS_2_1000_300_True                107             186           4673
FACE_AREAS_NORMALS_2_1000_3000_False             1451            1636            345
FACE_AREAS_NORMALS_2_1000_3000_True               107             186           4655
FACE_AREAS_NORMALS_10_100_300_False               767             918            653
FACE_AREAS_NORMALS_10_100_300_True                106             167           4712
FACE_AREAS_NORMALS_10_100_3000_False             7036            7754             72
FACE_AREAS_NORMALS_10_100_3000_True               113             164           4445
FACE_AREAS_NORMALS_10_1000_300_False              748             947            669
FACE_AREAS_NORMALS_10_1000_300_True               108             169           4638
FACE_AREAS_NORMALS_10_1000_3000_False            7069            7783             71
FACE_AREAS_NORMALS_10_1000_3000_True              108             172           4646
FACE_AREAS_NORMALS_32_100_300_False              2286            2496            219
FACE_AREAS_NORMALS_32_100_300_True                108             180           4631
FACE_AREAS_NORMALS_32_100_3000_False            23184           24369             22
FACE_AREAS_NORMALS_32_100_3000_True               159             213           3147
FACE_AREAS_NORMALS_32_1000_300_False             2414            2645            208
FACE_AREAS_NORMALS_32_1000_300_True               112             197           4480
FACE_AREAS_NORMALS_32_1000_3000_False           21687           22964             24
FACE_AREAS_NORMALS_32_1000_3000_True              141             211           3540
--------------------------------------------------------------------------------

Benchmark                                         Avg Time(μs)      Peak Time(μs) Iterations
--------------------------------------------------------------------------------
FACE_AREAS_NORMALS_TORCH_2_100_300_False               5465            5782             92
FACE_AREAS_NORMALS_TORCH_2_100_300_True                1198            1351            418
FACE_AREAS_NORMALS_TORCH_2_100_3000_False             48228           48869             11
FACE_AREAS_NORMALS_TORCH_2_100_3000_True               1186            1304            422
FACE_AREAS_NORMALS_TORCH_2_1000_300_False              5556            6097             90
FACE_AREAS_NORMALS_TORCH_2_1000_300_True               1200            1328            417
FACE_AREAS_NORMALS_TORCH_2_1000_3000_False            48683           50016             11
FACE_AREAS_NORMALS_TORCH_2_1000_3000_True              1185            1306            422
FACE_AREAS_NORMALS_TORCH_10_100_300_False             24215           25097             21
FACE_AREAS_NORMALS_TORCH_10_100_300_True               1150            1314            435
FACE_AREAS_NORMALS_TORCH_10_100_3000_False           232605          234952              3
FACE_AREAS_NORMALS_TORCH_10_100_3000_True              1193            1314            420
FACE_AREAS_NORMALS_TORCH_10_1000_300_False            24912           25343             21
FACE_AREAS_NORMALS_TORCH_10_1000_300_True              1216            1330            412
FACE_AREAS_NORMALS_TORCH_10_1000_3000_False          239907          241253              3
FACE_AREAS_NORMALS_TORCH_10_1000_3000_True             1226            1333            408
FACE_AREAS_NORMALS_TORCH_32_100_300_False             73991           75776              7
FACE_AREAS_NORMALS_TORCH_32_100_300_True               1193            1339            420
FACE_AREAS_NORMALS_TORCH_32_100_3000_False           728932          728932              1
FACE_AREAS_NORMALS_TORCH_32_100_3000_True              1186            1359            422
FACE_AREAS_NORMALS_TORCH_32_1000_300_False            76385           79129              7
FACE_AREAS_NORMALS_TORCH_32_1000_300_True              1165            1310            430
FACE_AREAS_NORMALS_TORCH_32_1000_3000_False          753276          753276              1
FACE_AREAS_NORMALS_TORCH_32_1000_3000_True             1205            1340            415
--------------------------------------------------------------------------------
```

Reviewed By: bottler, jcjohnson

Differential Revision: D19864385

fbshipit-source-id: 3a87ae41a8e3ab5560febcb94961798f2e09dfb8

29cd181a

Single function to load meshes from OBJs. join_meshes. · 8fe65d5f

Jeremy Reizenstein authored Feb 13, 2020

Summary:
Create the textures and the Meshes object from OBJ files in a single call.

There is functionality in OBJ files (like normals) which is ignored by this function.

Reviewed By: gkioxari

Differential Revision: D19691699

fbshipit-source-id: e26442ed80ff231b65b17d6c54c9d41e22b4e4a3

8fe65d5f

11 Feb, 2020 2 commits

remove print statements · 23bb2795

Jeremy Reizenstein authored Feb 11, 2020

Reviewed By: gkioxari

Differential Revision: D19834684

fbshipit-source-id: 553dbf84d1062149b4915d313fc0f96eb047798c

23bb2795

Update tutorials for Google Colab · 09992a38

Nikhila Ravi authored Feb 10, 2020

Summary:
Update all colab notebooks to:
- Install pytorch3d using pip install from github.
- Retrieve data using `wget`. I set the wget commands to save the files in the same directory structure as in the PyTorch3d repo so that the rest of the tutorial would work for running locally or on Colab.

This should resolve the issues on GitHub with running the colab notebooks.

Reviewed By: gkioxari

Differential Revision: D19827450

fbshipit-source-id: d7b338597ddfd9a84c24592d4dccd274cae11d05

09992a38

10 Feb, 2020 1 commit

fix small typo in deform_source_mesh_to_target_mesh.ipynb (#34) · 3b1a0741

uzkt authored Feb 10, 2020

Summary:
fixed target object data folder path './data/doplhin'-> './data/dolphin'
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/34

Differential Revision: D19815377

Pulled By: nikhilaravi

fbshipit-source-id: ff17f6aef8d835b11d7803e912a311c7118b03fa

3b1a0741

08 Feb, 2020 2 commits

ignore cuda for cpu only installation · dcb09480

Nikhila Ravi authored Feb 08, 2020

Summary:
Added if `WITH_CUDA` checks for points/mesh rasterization. If installing on cpu only then this causes `Undefined symbol` errors when trying to import pytorch3d.

We had these checks for all the other cuda files but not the rasterization files.

Thanks ppwwyyxx for the tip!

Reviewed By: ppwwyyxx, gkioxari

Differential Revision: D19801495

fbshipit-source-id: 20e7adccfdb33ac731c00a89414b2beaf0a35529

dcb09480

small typo in deform_source_mesh_to_target_mesh.ipynb (#24) · ca588a59

Yannick Soom authored Feb 07, 2020

Summary:
fixed small typo in deform_source_mesh_to_target_mesh.ipynb
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/24

Differential Revision: D19801629

Pulled By: nikhilaravi

fbshipit-source-id: 59459f701e0a4c02e749a1b594ca77935fd037d1

ca588a59

07 Feb, 2020 3 commits

fix small typo in README.md (#21) · a2c68b15

Ignacio López-Francos authored Feb 07, 2020

Summary:
the dot at the pip command was outside of the inline code formatting. I just moved the back tick after the dot.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/21

Differential Revision: D19791603

Pulled By: nikhilaravi

fbshipit-source-id: 6b0bedd2a788aef0d9678f9c1c25354ada76a3f4

a2c68b15

Added single quote to the markdown block (#23) · b7786681

frederikzt authored Feb 07, 2020

Summary:
The missing single quote makes you unable to directly cope the line if code into Colab
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/23

Differential Revision: D19791643

Pulled By: nikhilaravi

fbshipit-source-id: 2aa043ad4163eb7146c7b8b00bd8846ae61d8009

b7786681

remove dataclass for python 3.6 compatibility. · 533887a1

Jeremy Reizenstein authored Feb 06, 2020

Summary: Make RasterizationSettings be a NamedTuple instead of a dataclass. This makes the mesh renderer work with python 3.6.

Reviewed By: nikhilaravi

Differential Revision: D19769924

fbshipit-source-id: db839f3506dda7d3344fb8a101fa75bdf139ce39

533887a1

05 Feb, 2020 3 commits

update website css on mobile · 3c9f0658

Nikhila Ravi authored Feb 05, 2020

Summary: Updated media queries for website on mobile.

Reviewed By: gkioxari

Differential Revision: D19745526

fbshipit-source-id: a8dc25fcc04726056231d2e1ebeb581251be9324

3c9f0658

website updates · 10ec66da

Nikhila Ravi authored Feb 05, 2020

Summary:
A few minor updates to the website.
- fix the color gradient on the homepage
- fix unicode escape for the copyright symbol

Reviewed By: gkioxari

Differential Revision: D19744165

fbshipit-source-id: 31068bd0b408fe7b298e1f69d9998d64498e9d8c

10ec66da

Setup website with docusaurus (#11) · 15d3a455

Nikhila Ravi authored Feb 04, 2020

Summary:
Set up landing page, docs page, and html versions of the ipython notebook tutorials.
Pull Request resolved: https://github.com/fairinternal/pytorch3d/pull/11

Reviewed By: gkioxari

Differential Revision: D19730380

Pulled By: nikhilaravi

fbshipit-source-id: 5df8d3f2ac2f8dce4d51f5d14fc336508c2fd0ea

15d3a455

03 Feb, 2020 1 commit

Add CPU implementation for nearest neighbor · e290f87c

Justin Johnson authored Feb 03, 2020

Summary:
Adds a CPU implementation for `pytorch3d.ops.nn_points_idx`.

Also renames the associated C++ and CUDA functions to use `AllCaps` names used in other C++ / CUDA code.

Reviewed By: gkioxari

Differential Revision: D19670491

fbshipit-source-id: 1b6409404025bf05e6a93f5d847e35afc9062f05

e290f87c

31 Jan, 2020 2 commits

update install.md · 25c2f340

Haoqi Fan authored Jan 31, 2020

Reviewed By: bottler, wanyenlo

Differential Revision: D19658045

fbshipit-source-id: a623a81c1ed1fa4054ea55bf06a2926e297b7966

25c2f340

load texture flag · 659ad343

Georgia Gkioxari authored Jan 31, 2020

Summary: Add flag for loading textures

Reviewed By: nikhilaravi

Differential Revision: D19664437

fbshipit-source-id: 3cc4e6179df9b7e24efff9e7da3b164253f1d775

659ad343

27 Jan, 2020 1 commit

allow packaging tools to override CUDA settings · 244b7eb8

Jeremy Reizenstein authored Jan 27, 2020

Summary: This makes sure circle ci builds work with cuda even on machines with no gpu.

Reviewed By: gkioxari

Differential Revision: D19543957

fbshipit-source-id: 9cbfcd4fca22ebe89434ffa71c25d75dd18d2eb6

244b7eb8

24 Jan, 2020 4 commits

fix conda install cmd in INSTALL.md · 674ee44c

Yun Chen authored Jan 24, 2020

Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/8

Differential Revision: D19556466

Pulled By: nikhilaravi

fbshipit-source-id: 26aa361882b688e7cd159e0d7d8cfad37d0049c1

674ee44c

fix link to tutorials in readme · d46e7fa1

Yun Chen authored Jan 24, 2020

Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/7

Differential Revision: D19556384

Pulled By: nikhilaravi

fbshipit-source-id: 4bd93a3bff92cbba78600bda703a19fd1c663109

d46e7fa1

update requirements.txt for readthedocs (#6) · fd9df742

Nikhila Ravi authored Jan 23, 2020

Summary:
We need to install pytorch3d in RTD. Update requirements.txt accordingly.
Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/6

Reviewed By: gkioxari

Differential Revision: D19549348

Pulled By: nikhilaravi

fbshipit-source-id: d8d6efe0af9c0d4c7cc6f7662d392f5b3bc16a8c

fd9df742

add docs/requirements.txt for readthedocs.io · 1af6af9b

Nikhila Ravi authored Jan 23, 2020

Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/5

Reviewed By: gkioxari

Differential Revision: D19548185

Pulled By: nikhilaravi

fbshipit-source-id: edc825d483a29f1a3311d46b4f349a6bc330c085

1af6af9b

23 Jan, 2020 2 commits

update conf.py for readthedocs · 349a499f

Nikhila Ravi authored Jan 23, 2020

Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/4

Differential Revision: D19546949

Pulled By: nikhilaravi

fbshipit-source-id: ce30785322a60c408fd6aa2f1cd3eb5d07015c7b

349a499f

Initial commit · dbf06b50
facebook-github-bot authored Jan 23, 2020
```
fbshipit-source-id: ad58e416e3ceeca85fae0583308968d04e78fe0d
```
dbf06b50