mirror of
https://github.com/nerfstudio-project/nerfstudio.git
synced 2026-11-13 19:33:46 +08:00
Ethan Weber
457788d689
* renaming dataloader to data. adding some dataloader classes * restructuring configs * fixed instant ngp tcnn direction rescaling * working through test cases * black and lint and tests
44 lines
1.6 KiB
Python
44 lines
1.6 KiB
Python
"""
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Test the camera classes.
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"""
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import torch
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from pyrad.cameras.cameras import EquirectangularCamera, PinholeCamera
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from pyrad.cameras.rays import RayBundle
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def test_pinhole_camera():
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"""Test that the pinhole camera model works."""
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pinhole_camera = PinholeCamera(cx=400.0, cy=400.0, fx=10.0, fy=10.0)
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camera_ray_bundle = pinhole_camera.get_camera_ray_bundle()
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assert isinstance(camera_ray_bundle, RayBundle)
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assert torch.allclose(camera_ray_bundle.origins[0], torch.tensor([0.0, 0.0, 0.0]))
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# Test generate rays on 1D input
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num_rays = 10
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intrinsics = torch.ones(num_rays, 4) # (num_rays, num_intrinsics_params)
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camera_to_world = torch.ones(num_rays, 3, 4) # (num_rays, 3, 4)
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coords = torch.ones(num_rays, 2)
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pinhole_camera.generate_rays(intrinsics, camera_to_world, coords)
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def test_equirectangular_camera():
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"""Test that the equirectangular camera model works."""
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equirectangular_camera = EquirectangularCamera(height=400, width=400)
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camera_ray_bundle = equirectangular_camera.get_camera_ray_bundle()
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assert isinstance(camera_ray_bundle, RayBundle)
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assert torch.allclose(camera_ray_bundle.origins[0], torch.tensor([0.0, 0.0, 0.0]))
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# Test generate rays on 1D input
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num_rays = 10
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intrinsics = torch.ones(num_rays, 2) * 20 # (num_rays, num_intrinsics_params)
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camera_to_world = torch.ones(num_rays, 3, 4) # (num_rays, 3, 4)
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coords = torch.ones(num_rays, 2)
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equirectangular_camera.generate_rays(intrinsics, camera_to_world, coords)
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if __name__ == "__main__":
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test_pinhole_camera()
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test_equirectangular_camera()
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