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https://github.com/facebookresearch/pytorch3d.git
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b19fe1de2f
Summary: This diff integrates the pulsar renderer source code into PyTorch3D as an alternative backend for the PyTorch3D point renderer. This diff is the first of a series of three diffs to complete that migration and focuses on the packaging and integration of the source code. For more information about the pulsar backend, see the release notes and the paper (https://arxiv.org/abs/2004.07484). For information on how to use the backend, see the point cloud rendering notebook and the examples in the folder `docs/examples`. Tasks addressed in the following diffs: * Add the PyTorch3D interface, * Add notebook examples and documentation (or adapt the existing ones to feature both interfaces). Reviewed By: nikhilaravi Differential Revision: D23947736 fbshipit-source-id: a5e77b53e6750334db22aefa89b4c079cda1b443
51 lines
1.4 KiB
Python
Executable File
51 lines
1.4 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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"""
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This example demonstrates the most trivial, direct interface of the pulsar
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sphere renderer. It renders and saves an image with 10 random spheres.
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Output: basic.png.
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"""
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from os import path
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import imageio
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import torch
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from pytorch3d.renderer.points.pulsar import Renderer
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n_points = 10
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width = 1_000
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height = 1_000
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device = torch.device("cuda")
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renderer = Renderer(width, height, n_points).to(device)
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# Generate sample data.
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vert_pos = torch.rand(n_points, 3, dtype=torch.float32, device=device) * 10.0
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vert_pos[:, 2] += 25.0
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vert_pos[:, :2] -= 5.0
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vert_col = torch.rand(n_points, 3, dtype=torch.float32, device=device)
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vert_rad = torch.rand(n_points, dtype=torch.float32, device=device)
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cam_params = torch.tensor(
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[
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0.0,
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0.0,
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0.0, # Position 0, 0, 0 (x, y, z).
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0.0,
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0.0,
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0.0, # Rotation 0, 0, 0 (in axis-angle format).
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5.0, # Focal length in world size.
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2.0, # Sensor size in world size.
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],
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dtype=torch.float32,
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device=device,
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)
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# Render.
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image = renderer(
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vert_pos,
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vert_col,
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vert_rad,
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cam_params,
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1.0e-1, # Renderer blending parameter gamma, in [1., 1e-5].
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45.0, # Maximum depth.
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)
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print("Writing image to `%s`." % (path.abspath("basic.png")))
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imageio.imsave("basic.png", (image.cpu().detach() * 255.0).to(torch.uint8).numpy())
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