#include "rasterizer.h" void rasterizeTriangleCPU(int idx, float* vt0, float* vt1, float* vt2, int width, int height, INT64* zbuffer, float* d, float occlusion_truncation) { float x_min = std::min(vt0[0], std::min(vt1[0],vt2[0])); float x_max = std::max(vt0[0], std::max(vt1[0],vt2[0])); float y_min = std::min(vt0[1], std::min(vt1[1],vt2[1])); float y_max = std::max(vt0[1], std::max(vt1[1],vt2[1])); for (int px = x_min; px < x_max + 1; ++px) { if (px < 0 || px >= width) continue; for (int py = y_min; py < y_max + 1; ++py) { if (py < 0 || py >= height) continue; float vt[2] = {px + 0.5, py + 0.5}; float baryCentricCoordinate[3]; calculateBarycentricCoordinate(vt0, vt1, vt2, vt, baryCentricCoordinate); if (isBarycentricCoordInBounds(baryCentricCoordinate)) { int pixel = py * width + px; if (zbuffer == 0) { zbuffer[pixel] = (INT64)(idx + 1); continue; } float depth = baryCentricCoordinate[0] * vt0[2] + baryCentricCoordinate[1] * vt1[2] + baryCentricCoordinate[2] * vt2[2]; float depth_thres = 0; if (d) { depth_thres = d[pixel] * 0.49999f + 0.5f + occlusion_truncation; } int z_quantize = depth * (2<<17); INT64 token = (INT64)z_quantize * MAXINT + (INT64)(idx + 1); if (depth < depth_thres) continue; zbuffer[pixel] = std::min(zbuffer[pixel], token); } } } } void barycentricFromImgcoordCPU(float* V, int* F, int* findices, INT64* zbuffer, int width, int height, int num_vertices, int num_faces, float* barycentric_map, int pix) { INT64 f = zbuffer[pix] % MAXINT; if (f == (MAXINT-1)) { findices[pix] = 0; barycentric_map[pix * 3] = 0; barycentric_map[pix * 3 + 1] = 0; barycentric_map[pix * 3 + 2] = 0; return; } findices[pix] = f; f -= 1; float barycentric[3] = {0, 0, 0}; if (f >= 0) { float vt[2] = {float(pix % width) + 0.5f, float(pix / width) + 0.5f}; float* vt0_ptr = V + (F[f * 3] * 4); float* vt1_ptr = V + (F[f * 3 + 1] * 4); float* vt2_ptr = V + (F[f * 3 + 2] * 4); float vt0[2] = {(vt0_ptr[0] / vt0_ptr[3] * 0.5f + 0.5f) * (width - 1) + 0.5f, (0.5f + 0.5f * vt0_ptr[1] / vt0_ptr[3]) * (height - 1) + 0.5f}; float vt1[2] = {(vt1_ptr[0] / vt1_ptr[3] * 0.5f + 0.5f) * (width - 1) + 0.5f, (0.5f + 0.5f * vt1_ptr[1] / vt1_ptr[3]) * (height - 1) + 0.5f}; float vt2[2] = {(vt2_ptr[0] / vt2_ptr[3] * 0.5f + 0.5f) * (width - 1) + 0.5f, (0.5f + 0.5f * vt2_ptr[1] / vt2_ptr[3]) * (height - 1) + 0.5f}; calculateBarycentricCoordinate(vt0, vt1, vt2, vt, barycentric); barycentric[0] = barycentric[0] / vt0_ptr[3]; barycentric[1] = barycentric[1] / vt1_ptr[3]; barycentric[2] = barycentric[2] / vt2_ptr[3]; float w = 1.0f / (barycentric[0] + barycentric[1] + barycentric[2]); barycentric[0] *= w; barycentric[1] *= w; barycentric[2] *= w; } barycentric_map[pix * 3] = barycentric[0]; barycentric_map[pix * 3 + 1] = barycentric[1]; barycentric_map[pix * 3 + 2] = barycentric[2]; } void rasterizeImagecoordsKernelCPU(float* V, int* F, float* d, INT64* zbuffer, float occlusion_trunc, int width, int height, int num_vertices, int num_faces, int f) { float* vt0_ptr = V + (F[f * 3] * 4); float* vt1_ptr = V + (F[f * 3 + 1] * 4); float* vt2_ptr = V + (F[f * 3 + 2] * 4); float vt0[3] = {(vt0_ptr[0] / vt0_ptr[3] * 0.5f + 0.5f) * (width - 1) + 0.5f, (0.5f + 0.5f * vt0_ptr[1] / vt0_ptr[3]) * (height - 1) + 0.5f, vt0_ptr[2] / vt0_ptr[3] * 0.49999f + 0.5f}; float vt1[3] = {(vt1_ptr[0] / vt1_ptr[3] * 0.5f + 0.5f) * (width - 1) + 0.5f, (0.5f + 0.5f * vt1_ptr[1] / vt1_ptr[3]) * (height - 1) + 0.5f, vt1_ptr[2] / vt1_ptr[3] * 0.49999f + 0.5f}; float vt2[3] = {(vt2_ptr[0] / vt2_ptr[3] * 0.5f + 0.5f) * (width - 1) + 0.5f, (0.5f + 0.5f * vt2_ptr[1] / vt2_ptr[3]) * (height - 1) + 0.5f, vt2_ptr[2] / vt2_ptr[3] * 0.49999f + 0.5f}; rasterizeTriangleCPU(f, vt0, vt1, vt2, width, height, zbuffer, d, occlusion_trunc); } std::vector rasterize_image_cpu(torch::Tensor V, torch::Tensor F, torch::Tensor D, int width, int height, float occlusion_truncation, int use_depth_prior) { int num_faces = F.size(0); int num_vertices = V.size(0); auto options = torch::TensorOptions().dtype(torch::kInt32).requires_grad(false); auto INT64_options = torch::TensorOptions().dtype(torch::kInt64).requires_grad(false); auto findices = torch::zeros({height, width}, options); INT64 maxint = (INT64)MAXINT * (INT64)MAXINT + (MAXINT - 1); auto z_min = torch::ones({height, width}, INT64_options) * (long)maxint; if (!use_depth_prior) { for (int i = 0; i < num_faces; ++i) { rasterizeImagecoordsKernelCPU(V.data_ptr(), F.data_ptr(), 0, (INT64*)z_min.data_ptr(), occlusion_truncation, width, height, num_vertices, num_faces, i); } } else { for (int i = 0; i < num_faces; ++i) rasterizeImagecoordsKernelCPU(V.data_ptr(), F.data_ptr(), D.data_ptr(), (INT64*)z_min.data_ptr(), occlusion_truncation, width, height, num_vertices, num_faces, i); } auto float_options = torch::TensorOptions().dtype(torch::kFloat32).requires_grad(false); auto barycentric = torch::zeros({height, width, 3}, float_options); for (int i = 0; i < width * height; ++i) barycentricFromImgcoordCPU(V.data_ptr(), F.data_ptr(), findices.data_ptr(), (INT64*)z_min.data_ptr(), width, height, num_vertices, num_faces, barycentric.data_ptr(), i); return {findices, barycentric}; } std::vector rasterize_image(torch::Tensor V, torch::Tensor F, torch::Tensor D, int width, int height, float occlusion_truncation, int use_depth_prior) { int device_id = V.get_device(); if (device_id == -1) return rasterize_image_cpu(V, F, D, width, height, occlusion_truncation, use_depth_prior); else return rasterize_image_gpu(V, F, D, width, height, occlusion_truncation, use_depth_prior); } PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { m.def("rasterize_image", &rasterize_image, "Custom image rasterization"); m.def("build_hierarchy", &build_hierarchy, "Custom image rasterization"); m.def("build_hierarchy_with_feat", &build_hierarchy_with_feat, "Custom image rasterization"); }