1. 19 Sep, 2020 1 commit
  2. 24 Apr, 2020 2 commits
    • Michele Sanna's avatar
      a formula for bin size for images over 64x64 (#90) · f8acecb6
      Michele Sanna authored
      
      
      Summary:
      Signed-off-by: default avatarMichele Sanna <sanna@arrival.com>
      
      fixes the bin_size calculation with a formula for any image_size > 64. Matches the values chosen so far.
      
      simple test:
      
      ```
      import numpy as np
      import matplotlib.pyplot as plt
      
      image_size = np.arange(64, 2048)
      bin_size = np.where(image_size <= 64, 8, (2 ** np.maximum(np.ceil(np.log2(image_size)) - 4, 4)).astype(int))
      
      print(image_size)
      print(bin_size)
      
      for ims, bins in zip(image_size, bin_size):
          if ims <= 64:
              assert bins == 8
          elif ims <= 256:
              assert bins == 16
          elif ims <= 512:
              assert bins == 32
          elif ims <= 1024:
              assert bins == 64
          elif ims <= 2048:
              assert bins == 128
      
          assert (ims + bins - 1) // bins < 22
      
      plt.plot(image_size, bin_size)
      plt.grid()
      plt.show()
      ```
      
      ![img](https://user-images.githubusercontent.com/54891577/75464693-795bcf00-597f-11ea-9061-26440211691c.png)
      Pull Request resolved: https://github.com/facebookresearch/pytorch3d/pull/90
      
      Reviewed By: jcjohnson
      
      Differential Revision: D21160372
      
      Pulled By: nikhilaravi
      
      fbshipit-source-id: 660cf5832f4ca5be243c435a6bed969596fc0188
      f8acecb6
    • Nikhila Ravi's avatar
      Cuda updates · c3d636dc
      Nikhila Ravi authored
      Summary:
      Updates to:
      - enable cuda kernel launches on any GPU (not just the default)
      - cuda and contiguous checks for all kernels
      - checks to ensure all tensors are on the same device
      - error reporting in the cuda kernels
      - cuda tests now run on a random device not just the default
      
      Reviewed By: jcjohnson, gkioxari
      
      Differential Revision: D21215280
      
      fbshipit-source-id: 1bedc9fe6c35e9e920bdc4d78ed12865b1005519
      c3d636dc
  3. 20 Apr, 2020 1 commit
    • Nikhila Ravi's avatar
      coarse rasterization bug fix · 9ef1ee84
      Nikhila Ravi authored
      Summary:
      Fix a bug which resulted in a rendering artifacts if the image size was not a multiple of 16.
      Fix: Revert coarse rasterization to original implementation and only update fine rasterization to reverse the ordering of Y and X axis. This is much simpler than the previous approach!
      
      Additional changes:
      - updated mesh rendering end-end tests to check outputs from both naive and coarse to fine rasterization.
      - added pointcloud rendering end-end tests
      
      Reviewed By: gkioxari
      
      Differential Revision: D21102725
      
      fbshipit-source-id: 2e7e1b013dd6dd12b3a00b79eb8167deddb2e89a
      9ef1ee84
  4. 29 Mar, 2020 1 commit
    • Patrick Labatut's avatar
      Address black + isort fbsource linter warnings · d57daa6f
      Patrick Labatut authored
      Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff)
      
      Reviewed By: nikhilaravi
      
      Differential Revision: D20558373
      
      fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8
      d57daa6f
  5. 23 Mar, 2020 1 commit
    • Jeremy Reizenstein's avatar
      use assertClose · 595aca27
      Jeremy Reizenstein authored
      Summary: use assertClose in some tests, which enforces shape equality. Fixes some small problems, including graph_conv on an empty graph.
      
      Reviewed By: nikhilaravi
      
      Differential Revision: D20556912
      
      fbshipit-source-id: 60a61eafe3c03ce0f6c9c1a842685708fb10ac5b
      595aca27
  6. 18 Mar, 2020 1 commit