mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-02 03:42:50 +08:00
d220ee2f66
Summary: Changes to CI and some minor fixes now that pulsar is part of pytorch3d. Most significantly, add CUB to CI builds. Make CUB_HOME override the CUB already in cudatoolkit (important for cuda11.0 which uses cub 1.9.9 which pulsar doesn't work well with. Make imageio available for testing. Lint fixes. Fix some test verbosity. Avoid use of atomicAdd_block on older GPUs. Reviewed By: nikhilaravi, classner Differential Revision: D24773716 fbshipit-source-id: 2428356bb2e62735f2bc0c15cbe4cff35b1b24b8
72 lines
2.1 KiB
Python
Executable File
72 lines
2.1 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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import logging
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import math
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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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LOGGER = logging.getLogger(__name__)
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def cli():
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"""
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Basic example for the pulsar sphere renderer.
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Writes to `basic.png`.
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"""
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LOGGER.info("Rendering on GPU...")
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torch.manual_seed(1)
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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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# The PyTorch3D system is right handed; in pulsar you can choose the handedness.
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# For easy reproducibility we use a right handed coordinate system here.
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renderer = Renderer(width, height, n_points, right_handed_system=True).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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math.pi, # Because of the right handed system, the camera must look 'back'.
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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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LOGGER.info("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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LOGGER.info("Done.")
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if __name__ == "__main__":
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logging.basicConfig(level=logging.INFO)
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cli()
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