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https://github.com/facebookresearch/pytorch3d.git
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57a22e7306
Summary: Refactor cameras * CamerasBase was enhanced with `transform_points_screen` that transforms projected points from NDC to screen space * OpenGLPerspective, OpenGLOrthographic -> FoVPerspective, FoVOrthographic * SfMPerspective, SfMOrthographic -> Perspective, Orthographic * PerspectiveCamera can optionally be constructred with screen space parameters * Note on Cameras and coordinate systems was added Reviewed By: nikhilaravi Differential Revision: D23168525 fbshipit-source-id: dd138e2b2cc7e0e0d9f34c45b8251c01266a2063
46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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from itertools import product
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import torch
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from fvcore.common.benchmark import benchmark
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from pytorch3d.renderer.cameras import FoVPerspectiveCameras, look_at_view_transform
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from pytorch3d.renderer.mesh.rasterizer import MeshRasterizer
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from pytorch3d.utils.ico_sphere import ico_sphere
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def rasterize_transform_with_init(num_meshes: int, ico_level: int = 5, device="cuda"):
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# Init meshes
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sphere_meshes = ico_sphere(ico_level, device).extend(num_meshes)
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# Init transform
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R, T = look_at_view_transform(1.0, 0.0, 0.0)
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cameras = FoVPerspectiveCameras(device=device, R=R, T=T)
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# Init rasterizer
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rasterizer = MeshRasterizer(cameras=cameras)
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torch.cuda.synchronize()
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def raster_fn():
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rasterizer.transform(sphere_meshes)
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torch.cuda.synchronize()
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return raster_fn
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def bm_mesh_rasterizer_transform() -> None:
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if torch.cuda.is_available():
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kwargs_list = []
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num_meshes = [1, 8]
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ico_level = [0, 1, 3, 4]
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test_cases = product(num_meshes, ico_level)
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for case in test_cases:
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n, ic = case
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kwargs_list.append({"num_meshes": n, "ico_level": ic})
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benchmark(
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rasterize_transform_with_init,
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"MESH_RASTERIZER",
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kwargs_list,
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warmup_iters=1,
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)
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