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| __host__ __device__ inline float calculateSignedArea2(float* a, float* b, float* c) { | |
| return ((c[0] - a[0]) * (b[1] - a[1]) - (b[0] - a[0]) * (c[1] - a[1])); | |
| } | |
| __host__ __device__ inline void calculateBarycentricCoordinate(float* a, float* b, float* c, float* p, | |
| float* barycentric) | |
| { | |
| float beta_tri = calculateSignedArea2(a, p, c); | |
| float gamma_tri = calculateSignedArea2(a, b, p); | |
| float area = calculateSignedArea2(a, b, c); | |
| if (area == 0) { | |
| barycentric[0] = -1.0; | |
| barycentric[1] = -1.0; | |
| barycentric[2] = -1.0; | |
| return; | |
| } | |
| float tri_inv = 1.0 / area; | |
| float beta = beta_tri * tri_inv; | |
| float gamma = gamma_tri * tri_inv; | |
| float alpha = 1.0 - beta - gamma; | |
| barycentric[0] = alpha; | |
| barycentric[1] = beta; | |
| barycentric[2] = gamma; | |
| } | |
| __host__ __device__ inline bool isBarycentricCoordInBounds(float* barycentricCoord) { | |
| return barycentricCoord[0] >= 0.0 && barycentricCoord[0] <= 1.0 && | |
| barycentricCoord[1] >= 0.0 && barycentricCoord[1] <= 1.0 && | |
| barycentricCoord[2] >= 0.0 && barycentricCoord[2] <= 1.0; | |
| } | |
| std::vector<torch::Tensor> rasterize_image_gpu(torch::Tensor V, torch::Tensor F, torch::Tensor D, | |
| int width, int height, float occlusion_truncation, int use_depth_prior); | |
| std::vector<std::vector<torch::Tensor>> build_hierarchy(std::vector<torch::Tensor> view_layer_positions, std::vector<torch::Tensor> view_layer_normals, int num_level, int resolution); | |
| std::vector<std::vector<torch::Tensor>> build_hierarchy_with_feat( | |
| std::vector<torch::Tensor> view_layer_positions, | |
| std::vector<torch::Tensor> view_layer_normals, | |
| std::vector<torch::Tensor> view_layer_feats, | |
| int num_level, int resolution); | |