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pytorch3d
mirror of https://github.com/facebookresearch/pytorch3d
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11 Commits

Author SHA1 Message Date
Patrick Labatut af93f34834 License lint codebase 
Summary: License lint codebase

Reviewed By: theschnitz

Differential Revision: D29001799

fbshipit-source-id: 5c59869911785b0181b1663bbf430bc8b7fb2909
 2021-06-22 03:45:27 -07:00
Jeremy Reizenstein 124bb5e391 spelling 
Summary: Collection of spelling things, mostly in docs / tutorials.

Reviewed By: gkioxari

Differential Revision: D26101323

fbshipit-source-id: 652f62bc9d71a4ff872efa21141225e43191353a
 2021-04-09 09:58:54 -07:00
Jeremy Reizenstein 24ee279005 Fix flake exceptions 
Summary: flake8 no longer respects the black fmt:off message, so include specific line-length exclusion.

Reviewed By: nikhilaravi

Differential Revision: D27624641

fbshipit-source-id: adcdb6f55b382fbf252eede3f3ddeda0621da883
 2021-04-08 09:38:43 -07:00
Nikhila Ravi 3d769a66cb Non Square image rasterization for pointclouds 
Summary:
Similar to non square image rasterization for meshes, apply the same updates to the pointcloud rasterizer.

Main API Change:
- PointRasterizationSettings now accepts a tuple/list of (H, W) for the image size.

Reviewed By: jcjohnson

Differential Revision: D25465206

fbshipit-source-id: 7370d83c431af1b972158cecae19d82364623380
 2020-12-15 14:15:32 -08:00
Nikhila Ravi ebe2693b11 Support variable size radius for points in rasterizer 
Summary:
Support variable size pointclouds in the renderer API to allow compatibility with Pulsar rasterizer.

If radius is provided as a float, it is converted to a tensor of shape (P). Otherwise radius is expected to be an (N, P_padded) dimensional tensor where P_padded is the max number of points in the batch (following the convention from pulsar: https://our.intern.facebook.com/intern/diffusion/FBS/browse/master/fbcode/frl/gemini/pulsar/pulsar/renderer.py?commit=ee0342850210e5df441e14fd97162675c70d147c&lines=50)

Reviewed By: jcjohnson, gkioxari

Differential Revision: D21429400

fbshipit-source-id: 65de7d9cd2472b27fc29f96160c33687e88098a2
 2020-09-18 18:48:18 -07:00
Michele Sanna f8acecb6b3 a formula for bin size for images over 64x64 (#90) 
Summary:
Signed-off-by: Michele 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
 2020-04-24 14:56:41 -07:00
Nikhila Ravi c3d636dc8c Cuda updates 
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
 2020-04-24 09:11:04 -07:00
Nikhila Ravi 9ef1ee8455 coarse rasterization bug fix 
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
 2020-04-20 14:54:16 -07:00
Patrick Labatut d57daa6f85 Address black + isort fbsource linter warnings 
Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff)

Reviewed By: nikhilaravi

Differential Revision: D20558373

fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8
 2020-03-29 14:51:02 -07:00
Jeremy Reizenstein 595aca27ea use assertClose 
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
 2020-03-23 11:36:38 -07:00
Nikhila Ravi 3d3b2fdc46 Re-sync with internal repository 2020-03-18 10:35:27 -07:00