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https://github.com/nerfstudio-project/nerfstudio.git
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Ethan Weber
8973039e65
* misc cuda improvements. added cone angle as param * wandb as default. better organization for experiments * turn off tensorboard * disable eval when using viewer * remove comment * launch.json
118 lines
3.3 KiB
Plaintext
118 lines
3.3 KiB
Plaintext
#include "include/helpers_cuda.h"
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template <typename scalar_t>
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inline __host__ __device__ void _ray_aabb_intersect(
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const scalar_t* rays_o,
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const scalar_t* rays_d,
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const scalar_t* aabb,
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scalar_t* near,
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scalar_t* far
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) {
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// aabb is [xmin, ymin, zmin, xmax, ymax, zmax]
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scalar_t tmin = (aabb[0] - rays_o[0]) / rays_d[0];
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scalar_t tmax = (aabb[3] - rays_o[0]) / rays_d[0];
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if (tmin > tmax) __swap(tmin, tmax);
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scalar_t tymin = (aabb[1] - rays_o[1]) / rays_d[1];
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scalar_t tymax = (aabb[4] - rays_o[1]) / rays_d[1];
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if (tymin > tymax) __swap(tymin, tymax);
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if (tmin > tymax || tymin > tmax){
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*near = 1e10;
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*far = 1e10;
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return;
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}
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if (tymin > tmin) tmin = tymin;
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if (tymax < tmax) tmax = tymax;
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scalar_t tzmin = (aabb[2] - rays_o[2]) / rays_d[2];
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scalar_t tzmax = (aabb[5] - rays_o[2]) / rays_d[2];
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if (tzmin > tzmax) __swap(tzmin, tzmax);
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if (tmin > tzmax || tzmin > tmax){
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*near = 1e10;
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*far = 1e10;
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return;
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}
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if (tzmin > tmin) tmin = tzmin;
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if (tzmax < tmax) tmax = tzmax;
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*near = tmin;
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*far = tmax;
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return;
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}
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template <typename scalar_t>
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__global__ void kernel_ray_aabb_intersect(
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const int N,
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const scalar_t* rays_o,
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const scalar_t* rays_d,
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const scalar_t* aabb,
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scalar_t* t_min,
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scalar_t* t_max
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){
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// aabb is [xmin, ymin, zmin, xmax, ymax, zmax]
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CUDA_GET_THREAD_ID(thread_id, N);
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// locate
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rays_o += thread_id * 3;
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rays_d += thread_id * 3;
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t_min += thread_id;
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t_max += thread_id;
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_ray_aabb_intersect<scalar_t>(rays_o, rays_d, aabb, t_min, t_max);
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scalar_t zero = static_cast<scalar_t>(0.f);
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*t_min = *t_min > zero ? *t_min : zero;
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return;
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}
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/**
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* @brief Ray AABB Test
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*
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* @param rays_o Ray origins. Tensor with shape [N, 3].
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* @param rays_d Normalized ray directions. Tensor with shape [N, 3].
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* @param aabb Scene AABB [xmin, ymin, zmin, xmax, ymax, zmax]. Tensor with shape [6].
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* @return std::vector<torch::Tensor>
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* Ray AABB intersection {t_min, t_max} with shape [N] respectively. Note the t_min is
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* clipped to minimum zero.
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*/
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std::vector<torch::Tensor> ray_aabb_intersect(
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const torch::Tensor rays_o, const torch::Tensor rays_d, const torch::Tensor aabb
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) {
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DEVICE_GUARD(rays_o);
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CHECK_INPUT(rays_o);
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CHECK_INPUT(rays_d);
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CHECK_INPUT(aabb);
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TORCH_CHECK(rays_o.ndimension() == 2 & rays_o.size(1) == 3)
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TORCH_CHECK(rays_d.ndimension() == 2 & rays_d.size(1) == 3)
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TORCH_CHECK(aabb.ndimension() == 1 & aabb.size(0) == 6)
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const int N = rays_o.size(0);
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const int threads = 256;
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const int blocks = CUDA_N_BLOCKS_NEEDED(N, threads);
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torch::Tensor t_min = torch::empty({N}, rays_o.options());
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torch::Tensor t_max = torch::empty({N}, rays_o.options());
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AT_DISPATCH_FLOATING_TYPES_AND_HALF(
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rays_o.scalar_type(), "ray_aabb_intersect",
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([&] {
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kernel_ray_aabb_intersect<scalar_t><<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(
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N,
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rays_o.data_ptr<scalar_t>(),
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rays_d.data_ptr<scalar_t>(),
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aabb.data_ptr<scalar_t>(),
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t_min.data_ptr<scalar_t>(),
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t_max.data_ptr<scalar_t>()
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);
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})
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);
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return {t_min, t_max};
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} |