- 21 Feb, 2020 1 commit
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merayxu authored
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
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- 20 Feb, 2020 3 commits
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Georgia Gkioxari authored
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
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Patrick Labatut authored
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
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Nikhila Ravi authored
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
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- 19 Feb, 2020 3 commits
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Georgia Gkioxari authored
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
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Nikhila Ravi authored
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
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Jeremy Reizenstein authored
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
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- 18 Feb, 2020 2 commits
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Chr1k0 authored
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
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Junior Rojas authored
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/54 Differential Revision: D19951851 Pulled By: gkioxari fbshipit-source-id: cf41d5806c761639d1efa42a633404b248486c30
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- 14 Feb, 2020 1 commit
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Nikhila Ravi authored
Summary: Ran `dev/linter.sh`. Reviewed By: bottler Differential Revision: D19761062 fbshipit-source-id: 1a49abe4a5f2bc7641b2b46e254aa77e6a48aa7d
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- 13 Feb, 2020 2 commits
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Georgia Gkioxari authored
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
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Jeremy Reizenstein authored
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
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- 11 Feb, 2020 2 commits
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Jeremy Reizenstein authored
Reviewed By: gkioxari Differential Revision: D19834684 fbshipit-source-id: 553dbf84d1062149b4915d313fc0f96eb047798c
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Nikhila Ravi authored
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
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- 10 Feb, 2020 1 commit
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uzkt authored
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
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- 08 Feb, 2020 2 commits
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Nikhila Ravi authored
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
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Yannick Soom authored
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
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- 07 Feb, 2020 3 commits
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Ignacio López-Francos authored
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
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frederikzt authored
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
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Jeremy Reizenstein authored
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
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- 05 Feb, 2020 3 commits
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Nikhila Ravi authored
Summary: Updated media queries for website on mobile. Reviewed By: gkioxari Differential Revision: D19745526 fbshipit-source-id: a8dc25fcc04726056231d2e1ebeb581251be9324
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Nikhila Ravi authored
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
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Nikhila Ravi authored
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
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- 03 Feb, 2020 1 commit
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Justin Johnson authored
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
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- 31 Jan, 2020 2 commits
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Haoqi Fan authored
Reviewed By: bottler, wanyenlo Differential Revision: D19658045 fbshipit-source-id: a623a81c1ed1fa4054ea55bf06a2926e297b7966
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Georgia Gkioxari authored
Summary: Add flag for loading textures Reviewed By: nikhilaravi Differential Revision: D19664437 fbshipit-source-id: 3cc4e6179df9b7e24efff9e7da3b164253f1d775
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- 27 Jan, 2020 1 commit
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Jeremy Reizenstein authored
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
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- 24 Jan, 2020 4 commits
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Yun Chen authored
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/8 Differential Revision: D19556466 Pulled By: nikhilaravi fbshipit-source-id: 26aa361882b688e7cd159e0d7d8cfad37d0049c1
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Yun Chen authored
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/7 Differential Revision: D19556384 Pulled By: nikhilaravi fbshipit-source-id: 4bd93a3bff92cbba78600bda703a19fd1c663109
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Nikhila Ravi authored
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
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Nikhila Ravi authored
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/5 Reviewed By: gkioxari Differential Revision: D19548185 Pulled By: nikhilaravi fbshipit-source-id: edc825d483a29f1a3311d46b4f349a6bc330c085
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- 23 Jan, 2020 2 commits
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Nikhila Ravi authored
Summary: Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/4 Differential Revision: D19546949 Pulled By: nikhilaravi fbshipit-source-id: ce30785322a60c408fd6aa2f1cd3eb5d07015c7b
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facebook-github-bot authored
fbshipit-source-id: ad58e416e3ceeca85fae0583308968d04e78fe0d
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