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submodules/depth-diff-gaussian-rasterization-min/CMakeLists.txt

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+#
+# Copyright (C) 2023, Inria
+# GRAPHDECO research group, https://team.inria.fr/graphdeco
+# All rights reserved.
+#
+# This software is free for non-commercial, research and evaluation use 
+# under the terms of the LICENSE.md file.
+#
+# For inquiries contact  george.drettakis@inria.fr
+#
+
+cmake_minimum_required(VERSION 3.20)
+
+project(DiffRast LANGUAGES CUDA CXX)
+
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_EXTENSIONS OFF)
+set(CMAKE_CUDA_STANDARD 17)
+
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
+
+add_library(CudaRasterizer
+	cuda_rasterizer/backward.h
+	cuda_rasterizer/backward.cu
+	cuda_rasterizer/forward.h
+	cuda_rasterizer/forward.cu
+	cuda_rasterizer/auxiliary.h
+	cuda_rasterizer/rasterizer_impl.cu
+	cuda_rasterizer/rasterizer_impl.h
+	cuda_rasterizer/rasterizer.h
+)
+
+set_target_properties(CudaRasterizer PROPERTIES CUDA_ARCHITECTURES "70;75;86")
+
+target_include_directories(CudaRasterizer PUBLIC ${CMAKE_CURRENT_SOURCE_DIR}/cuda_rasterizer)
+target_include_directories(CudaRasterizer PRIVATE third_party/glm ${CMAKE_CUDA_TOOLKIT_INCLUDE_DIRECTORIES})

submodules/depth-diff-gaussian-rasterization-min/LICENSE.md

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+Gaussian-Splatting License  
+===========================  
+
+**Inria** and **the Max Planck Institut for Informatik (MPII)** hold all the ownership rights on the *Software* named **gaussian-splatting**.  
+The *Software* is in the process of being registered with the Agence pour la Protection des  
+Programmes (APP).  
+
+The *Software* is still being developed by the *Licensor*.  
+
+*Licensor*'s goal is to allow the research community to use, test and evaluate  
+the *Software*.  
+
+## 1.  Definitions  
+
+*Licensee* means any person or entity that uses the *Software* and distributes  
+its *Work*.  
+
+*Licensor* means the owners of the *Software*, i.e Inria and MPII  
+
+*Software* means the original work of authorship made available under this  
+License ie gaussian-splatting.  
+
+*Work* means the *Software* and any additions to or derivative works of the  
+*Software* that are made available under this License.  
+
+
+## 2.  Purpose  
+This license is intended to define the rights granted to the *Licensee* by  
+Licensors under the *Software*.  
+
+## 3.  Rights granted  
+
+For the above reasons Licensors have decided to distribute the *Software*.  
+Licensors grant non-exclusive rights to use the *Software* for research purposes  
+to research users (both academic and industrial), free of charge, without right  
+to sublicense.. The *Software* may be used "non-commercially", i.e., for research  
+and/or evaluation purposes only.  
+
+Subject to the terms and conditions of this License, you are granted a  
+non-exclusive, royalty-free, license to reproduce, prepare derivative works of,  
+publicly display, publicly perform and distribute its *Work* and any resulting  
+derivative works in any form.  
+
+## 4.  Limitations  
+
+**4.1 Redistribution.** You may reproduce or distribute the *Work* only if (a) you do  
+so under this License, (b) you include a complete copy of this License with  
+your distribution, and (c) you retain without modification any copyright,  
+patent, trademark, or attribution notices that are present in the *Work*.  
+
+**4.2 Derivative Works.** You may specify that additional or different terms apply  
+to the use, reproduction, and distribution of your derivative works of the *Work*  
+("Your Terms") only if (a) Your Terms provide that the use limitation in  
+Section 2 applies to your derivative works, and (b) you identify the specific  
+derivative works that are subject to Your Terms. Notwithstanding Your Terms,  
+this License (including the redistribution requirements in Section 3.1) will  
+continue to apply to the *Work* itself.  
+
+**4.3** Any other use without of prior consent of Licensors is prohibited. Research  
+users explicitly acknowledge having received from Licensors all information  
+allowing to appreciate the adequacy between of the *Software* and their needs and  
+to undertake all necessary precautions for its execution and use.  
+
+**4.4** The *Software* is provided both as a compiled library file and as source  
+code. In case of using the *Software* for a publication or other results obtained  
+through the use of the *Software*, users are strongly encouraged to cite the  
+corresponding publications as explained in the documentation of the *Software*.  
+
+## 5.  Disclaimer  
+
+THE USER CANNOT USE, EXPLOIT OR DISTRIBUTE THE *SOFTWARE* FOR COMMERCIAL PURPOSES  
+WITHOUT PRIOR AND EXPLICIT CONSENT OF LICENSORS. YOU MUST CONTACT INRIA FOR ANY  
+UNAUTHORIZED USE: stip-sophia.transfert@inria.fr . ANY SUCH ACTION WILL  
+CONSTITUTE A FORGERY. THIS *SOFTWARE* IS PROVIDED "AS IS" WITHOUT ANY WARRANTIES  
+OF ANY NATURE AND ANY EXPRESS OR IMPLIED WARRANTIES, WITH REGARDS TO COMMERCIAL  
+USE, PROFESSIONNAL USE, LEGAL OR NOT, OR OTHER, OR COMMERCIALISATION OR  
+ADAPTATION. UNLESS EXPLICITLY PROVIDED BY LAW, IN NO EVENT, SHALL INRIA OR THE  
+AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR  
+CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE  
+GOODS OR SERVICES, LOSS OF USE, DATA, OR PROFITS OR BUSINESS INTERRUPTION)  
+HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT  
+LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING FROM, OUT OF OR  
+IN CONNECTION WITH THE *SOFTWARE* OR THE USE OR OTHER DEALINGS IN THE *SOFTWARE*.  

submodules/depth-diff-gaussian-rasterization-min/README.md

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+# Differential Gaussian Rasterization
+
+Used as the rasterization engine for the paper "3D Gaussian Splatting for Real-Time Rendering of Radiance Fields". If you can make use of it in your own research, please be so kind to cite us.
+
+<section class="section" id="BibTeX">
+  <div class="container is-max-desktop content">
+    <h2 class="title">BibTeX</h2>
+    <pre><code>@Article{kerbl3Dgaussians,
+      author       = {Kerbl, Bernhard and Kopanas, Georgios and Leimk{\"u}hler, Thomas and Drettakis, George},
+      title        = {3D Gaussian Splatting for Real-Time Radiance Field Rendering},
+      journal      = {ACM Transactions on Graphics},
+      number       = {4},
+      volume       = {42},
+      month        = {July},
+      year         = {2023},
+      url          = {https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/}
+}</code></pre>
+  </div>
+</section>

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/auxiliary.h

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+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#ifndef CUDA_RASTERIZER_AUXILIARY_H_INCLUDED
+#define CUDA_RASTERIZER_AUXILIARY_H_INCLUDED
+
+#include "config.h"
+#include "stdio.h"
+
+#define BLOCK_SIZE (BLOCK_X * BLOCK_Y)
+#define NUM_WARPS (BLOCK_SIZE/32)
+
+// Spherical harmonics coefficients
+__device__ const float SH_C0 = 0.28209479177387814f;
+__device__ const float SH_C1 = 0.4886025119029199f;
+__device__ const float SH_C2[] = {
+	1.0925484305920792f,
+	-1.0925484305920792f,
+	0.31539156525252005f,
+	-1.0925484305920792f,
+	0.5462742152960396f
+};
+__device__ const float SH_C3[] = {
+	-0.5900435899266435f,
+	2.890611442640554f,
+	-0.4570457994644658f,
+	0.3731763325901154f,
+	-0.4570457994644658f,
+	1.445305721320277f,
+	-0.5900435899266435f
+};
+
+__forceinline__ __device__ float ndc2Pix(float v, int S)
+{
+	return ((v + 1.0) * S - 1.0) * 0.5;
+}
+
+__forceinline__ __device__ void getRect(const float2 p, int max_radius, uint2& rect_min, uint2& rect_max, dim3 grid)
+{
+	rect_min = {
+		min(grid.x, max((int)0, (int)((p.x - max_radius) / BLOCK_X))),
+		min(grid.y, max((int)0, (int)((p.y - max_radius) / BLOCK_Y)))
+	};
+	rect_max = {
+		min(grid.x, max((int)0, (int)((p.x + max_radius + BLOCK_X - 1) / BLOCK_X))),
+		min(grid.y, max((int)0, (int)((p.y + max_radius + BLOCK_Y - 1) / BLOCK_Y)))
+	};
+}
+
+__forceinline__ __device__ float3 transformPoint4x3(const float3& p, const float* matrix)
+{
+	float3 transformed = {
+		matrix[0] * p.x + matrix[4] * p.y + matrix[8] * p.z + matrix[12],
+		matrix[1] * p.x + matrix[5] * p.y + matrix[9] * p.z + matrix[13],
+		matrix[2] * p.x + matrix[6] * p.y + matrix[10] * p.z + matrix[14],
+	};
+	return transformed;
+}
+
+__forceinline__ __device__ float4 transformPoint4x4(const float3& p, const float* matrix)
+{
+	float4 transformed = {
+		matrix[0] * p.x + matrix[4] * p.y + matrix[8] * p.z + matrix[12],
+		matrix[1] * p.x + matrix[5] * p.y + matrix[9] * p.z + matrix[13],
+		matrix[2] * p.x + matrix[6] * p.y + matrix[10] * p.z + matrix[14],
+		matrix[3] * p.x + matrix[7] * p.y + matrix[11] * p.z + matrix[15]
+	};
+	return transformed;
+}
+
+__forceinline__ __device__ float3 transformVec4x3(const float3& p, const float* matrix)
+{
+	float3 transformed = {
+		matrix[0] * p.x + matrix[4] * p.y + matrix[8] * p.z,
+		matrix[1] * p.x + matrix[5] * p.y + matrix[9] * p.z,
+		matrix[2] * p.x + matrix[6] * p.y + matrix[10] * p.z,
+	};
+	return transformed;
+}
+
+__forceinline__ __device__ float3 transformVec4x3Transpose(const float3& p, const float* matrix)
+{
+	float3 transformed = {
+		matrix[0] * p.x + matrix[1] * p.y + matrix[2] * p.z,
+		matrix[4] * p.x + matrix[5] * p.y + matrix[6] * p.z,
+		matrix[8] * p.x + matrix[9] * p.y + matrix[10] * p.z,
+	};
+	return transformed;
+}
+
+__forceinline__ __device__ float dnormvdz(float3 v, float3 dv)
+{
+	float sum2 = v.x * v.x + v.y * v.y + v.z * v.z;
+	float invsum32 = 1.0f / sqrt(sum2 * sum2 * sum2);
+	float dnormvdz = (-v.x * v.z * dv.x - v.y * v.z * dv.y + (sum2 - v.z * v.z) * dv.z) * invsum32;
+	return dnormvdz;
+}
+
+__forceinline__ __device__ float3 dnormvdv(float3 v, float3 dv)
+{
+	float sum2 = v.x * v.x + v.y * v.y + v.z * v.z;
+	float invsum32 = 1.0f / sqrt(sum2 * sum2 * sum2);
+
+	float3 dnormvdv;
+	dnormvdv.x = ((+sum2 - v.x * v.x) * dv.x - v.y * v.x * dv.y - v.z * v.x * dv.z) * invsum32;
+	dnormvdv.y = (-v.x * v.y * dv.x + (sum2 - v.y * v.y) * dv.y - v.z * v.y * dv.z) * invsum32;
+	dnormvdv.z = (-v.x * v.z * dv.x - v.y * v.z * dv.y + (sum2 - v.z * v.z) * dv.z) * invsum32;
+	return dnormvdv;
+}
+
+__forceinline__ __device__ float4 dnormvdv(float4 v, float4 dv)
+{
+	float sum2 = v.x * v.x + v.y * v.y + v.z * v.z + v.w * v.w;
+	float invsum32 = 1.0f / sqrt(sum2 * sum2 * sum2);
+
+	float4 vdv = { v.x * dv.x, v.y * dv.y, v.z * dv.z, v.w * dv.w };
+	float vdv_sum = vdv.x + vdv.y + vdv.z + vdv.w;
+	float4 dnormvdv;
+	dnormvdv.x = ((sum2 - v.x * v.x) * dv.x - v.x * (vdv_sum - vdv.x)) * invsum32;
+	dnormvdv.y = ((sum2 - v.y * v.y) * dv.y - v.y * (vdv_sum - vdv.y)) * invsum32;
+	dnormvdv.z = ((sum2 - v.z * v.z) * dv.z - v.z * (vdv_sum - vdv.z)) * invsum32;
+	dnormvdv.w = ((sum2 - v.w * v.w) * dv.w - v.w * (vdv_sum - vdv.w)) * invsum32;
+	return dnormvdv;
+}
+
+__forceinline__ __device__ float sigmoid(float x)
+{
+	return 1.0f / (1.0f + expf(-x));
+}
+
+__forceinline__ __device__ bool in_frustum(int idx,
+	const float* orig_points,
+	const float* viewmatrix,
+	const float* projmatrix,
+	bool prefiltered,
+	float3& p_view)
+{
+	float3 p_orig = { orig_points[3 * idx], orig_points[3 * idx + 1], orig_points[3 * idx + 2] };
+
+	// Bring points to screen space
+	float4 p_hom = transformPoint4x4(p_orig, projmatrix);
+	float p_w = 1.0f / (p_hom.w + 0.0000001f);
+	float3 p_proj = { p_hom.x * p_w, p_hom.y * p_w, p_hom.z * p_w };
+	p_view = transformPoint4x3(p_orig, viewmatrix);
+
+	if (p_view.z <= 0.2f)// || ((p_proj.x < -1.3 || p_proj.x > 1.3 || p_proj.y < -1.3 || p_proj.y > 1.3)))
+	{
+		if (prefiltered)
+		{
+			printf("Point is filtered although prefiltered is set. This shouldn't happen!");
+			__trap();
+		}
+		return false;
+	}
+	return true;
+}
+
+#define CHECK_CUDA(A, debug) \
+A; if(debug) { \
+auto ret = cudaDeviceSynchronize(); \
+if (ret != cudaSuccess) { \
+std::cerr << "\n[CUDA ERROR] in " << __FILE__ << "\nLine " << __LINE__ << ": " << cudaGetErrorString(ret); \
+throw std::runtime_error(cudaGetErrorString(ret)); \
+} \
+}
+
+#endif

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/backward.cu

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+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#include "backward.h"
+#include "auxiliary.h"
+#include <cooperative_groups.h>
+#include <cooperative_groups/reduce.h>
+namespace cg = cooperative_groups;
+
+// Backward pass for conversion of spherical harmonics to RGB for
+// each Gaussian.
+__device__ void computeColorFromSH(int idx, int deg, int max_coeffs, const glm::vec3* means, glm::vec3 campos, const float* shs, const bool* clamped, const glm::vec3* dL_dcolor, glm::vec3* dL_dmeans, glm::vec3* dL_dshs)
+{
+	// Compute intermediate values, as it is done during forward
+	glm::vec3 pos = means[idx];
+	glm::vec3 dir_orig = pos - campos;
+	glm::vec3 dir = dir_orig / glm::length(dir_orig);
+
+	glm::vec3* sh = ((glm::vec3*)shs) + idx * max_coeffs;
+
+	// Use PyTorch rule for clamping: if clamping was applied,
+	// gradient becomes 0.
+	glm::vec3 dL_dRGB = dL_dcolor[idx];
+	dL_dRGB.x *= clamped[3 * idx + 0] ? 0 : 1;
+	dL_dRGB.y *= clamped[3 * idx + 1] ? 0 : 1;
+	dL_dRGB.z *= clamped[3 * idx + 2] ? 0 : 1;
+
+	glm::vec3 dRGBdx(0, 0, 0);
+	glm::vec3 dRGBdy(0, 0, 0);
+	glm::vec3 dRGBdz(0, 0, 0);
+	float x = dir.x;
+	float y = dir.y;
+	float z = dir.z;
+
+	// Target location for this Gaussian to write SH gradients to
+	glm::vec3* dL_dsh = dL_dshs + idx * max_coeffs;
+
+	// No tricks here, just high school-level calculus.
+	float dRGBdsh0 = SH_C0;
+	dL_dsh[0] = dRGBdsh0 * dL_dRGB;
+	if (deg > 0)
+	{
+		float dRGBdsh1 = -SH_C1 * y;
+		float dRGBdsh2 = SH_C1 * z;
+		float dRGBdsh3 = -SH_C1 * x;
+		dL_dsh[1] = dRGBdsh1 * dL_dRGB;
+		dL_dsh[2] = dRGBdsh2 * dL_dRGB;
+		dL_dsh[3] = dRGBdsh3 * dL_dRGB;
+
+		dRGBdx = -SH_C1 * sh[3];
+		dRGBdy = -SH_C1 * sh[1];
+		dRGBdz = SH_C1 * sh[2];
+
+		if (deg > 1)
+		{
+			float xx = x * x, yy = y * y, zz = z * z;
+			float xy = x * y, yz = y * z, xz = x * z;
+
+			float dRGBdsh4 = SH_C2[0] * xy;
+			float dRGBdsh5 = SH_C2[1] * yz;
+			float dRGBdsh6 = SH_C2[2] * (2.f * zz - xx - yy);
+			float dRGBdsh7 = SH_C2[3] * xz;
+			float dRGBdsh8 = SH_C2[4] * (xx - yy);
+			dL_dsh[4] = dRGBdsh4 * dL_dRGB;
+			dL_dsh[5] = dRGBdsh5 * dL_dRGB;
+			dL_dsh[6] = dRGBdsh6 * dL_dRGB;
+			dL_dsh[7] = dRGBdsh7 * dL_dRGB;
+			dL_dsh[8] = dRGBdsh8 * dL_dRGB;
+
+			dRGBdx += SH_C2[0] * y * sh[4] + SH_C2[2] * 2.f * -x * sh[6] + SH_C2[3] * z * sh[7] + SH_C2[4] * 2.f * x * sh[8];
+			dRGBdy += SH_C2[0] * x * sh[4] + SH_C2[1] * z * sh[5] + SH_C2[2] * 2.f * -y * sh[6] + SH_C2[4] * 2.f * -y * sh[8];
+			dRGBdz += SH_C2[1] * y * sh[5] + SH_C2[2] * 2.f * 2.f * z * sh[6] + SH_C2[3] * x * sh[7];
+
+			if (deg > 2)
+			{
+				float dRGBdsh9 = SH_C3[0] * y * (3.f * xx - yy);
+				float dRGBdsh10 = SH_C3[1] * xy * z;
+				float dRGBdsh11 = SH_C3[2] * y * (4.f * zz - xx - yy);
+				float dRGBdsh12 = SH_C3[3] * z * (2.f * zz - 3.f * xx - 3.f * yy);
+				float dRGBdsh13 = SH_C3[4] * x * (4.f * zz - xx - yy);
+				float dRGBdsh14 = SH_C3[5] * z * (xx - yy);
+				float dRGBdsh15 = SH_C3[6] * x * (xx - 3.f * yy);
+				dL_dsh[9] = dRGBdsh9 * dL_dRGB;
+				dL_dsh[10] = dRGBdsh10 * dL_dRGB;
+				dL_dsh[11] = dRGBdsh11 * dL_dRGB;
+				dL_dsh[12] = dRGBdsh12 * dL_dRGB;
+				dL_dsh[13] = dRGBdsh13 * dL_dRGB;
+				dL_dsh[14] = dRGBdsh14 * dL_dRGB;
+				dL_dsh[15] = dRGBdsh15 * dL_dRGB;
+
+				dRGBdx += (
+					SH_C3[0] * sh[9] * 3.f * 2.f * xy +
+					SH_C3[1] * sh[10] * yz +
+					SH_C3[2] * sh[11] * -2.f * xy +
+					SH_C3[3] * sh[12] * -3.f * 2.f * xz +
+					SH_C3[4] * sh[13] * (-3.f * xx + 4.f * zz - yy) +
+					SH_C3[5] * sh[14] * 2.f * xz +
+					SH_C3[6] * sh[15] * 3.f * (xx - yy));
+
+				dRGBdy += (
+					SH_C3[0] * sh[9] * 3.f * (xx - yy) +
+					SH_C3[1] * sh[10] * xz +
+					SH_C3[2] * sh[11] * (-3.f * yy + 4.f * zz - xx) +
+					SH_C3[3] * sh[12] * -3.f * 2.f * yz +
+					SH_C3[4] * sh[13] * -2.f * xy +
+					SH_C3[5] * sh[14] * -2.f * yz +
+					SH_C3[6] * sh[15] * -3.f * 2.f * xy);
+
+				dRGBdz += (
+					SH_C3[1] * sh[10] * xy +
+					SH_C3[2] * sh[11] * 4.f * 2.f * yz +
+					SH_C3[3] * sh[12] * 3.f * (2.f * zz - xx - yy) +
+					SH_C3[4] * sh[13] * 4.f * 2.f * xz +
+					SH_C3[5] * sh[14] * (xx - yy));
+			}
+		}
+	}
+
+	// The view direction is an input to the computation. View direction
+	// is influenced by the Gaussian's mean, so SHs gradients
+	// must propagate back into 3D position.
+	glm::vec3 dL_ddir(glm::dot(dRGBdx, dL_dRGB), glm::dot(dRGBdy, dL_dRGB), glm::dot(dRGBdz, dL_dRGB));
+
+	// Account for normalization of direction
+	float3 dL_dmean = dnormvdv(float3{ dir_orig.x, dir_orig.y, dir_orig.z }, float3{ dL_ddir.x, dL_ddir.y, dL_ddir.z });
+
+	// Gradients of loss w.r.t. Gaussian means, but only the portion 
+	// that is caused because the mean affects the view-dependent color.
+	// Additional mean gradient is accumulated in below methods.
+	dL_dmeans[idx] += glm::vec3(dL_dmean.x, dL_dmean.y, dL_dmean.z);
+}
+
+// Backward version of INVERSE 2D covariance matrix computation
+// (due to length launched as separate kernel before other 
+// backward steps contained in preprocess)
+__global__ void computeCov2DCUDA(int P,
+	const float3* means,
+	const int* radii,
+	const float* cov3Ds,
+	const float h_x, float h_y,
+	const float tan_fovx, float tan_fovy,
+	const float* view_matrix,
+	const float* dL_dconics,
+	float3* dL_dmeans,
+	float* dL_dcov)
+{
+	auto idx = cg::this_grid().thread_rank();
+	if (idx >= P || !(radii[idx] > 0))
+		return;
+
+	// Reading location of 3D covariance for this Gaussian
+	const float* cov3D = cov3Ds + 6 * idx;
+
+	// Fetch gradients, recompute 2D covariance and relevant 
+	// intermediate forward results needed in the backward.
+	float3 mean = means[idx];
+	float3 dL_dconic = { dL_dconics[4 * idx], dL_dconics[4 * idx + 1], dL_dconics[4 * idx + 3] };
+	float3 t = transformPoint4x3(mean, view_matrix);
+	
+	const float limx = 1.3f * tan_fovx;
+	const float limy = 1.3f * tan_fovy;
+	const float txtz = t.x / t.z;
+	const float tytz = t.y / t.z;
+	t.x = min(limx, max(-limx, txtz)) * t.z;
+	t.y = min(limy, max(-limy, tytz)) * t.z;
+	
+	const float x_grad_mul = txtz < -limx || txtz > limx ? 0 : 1;
+	const float y_grad_mul = tytz < -limy || tytz > limy ? 0 : 1;
+
+	glm::mat3 J = glm::mat3(h_x / t.z, 0.0f, -(h_x * t.x) / (t.z * t.z),
+		0.0f, h_y / t.z, -(h_y * t.y) / (t.z * t.z),
+		0, 0, 0);
+
+	glm::mat3 W = glm::mat3(
+		view_matrix[0], view_matrix[4], view_matrix[8],
+		view_matrix[1], view_matrix[5], view_matrix[9],
+		view_matrix[2], view_matrix[6], view_matrix[10]);
+
+	glm::mat3 Vrk = glm::mat3(
+		cov3D[0], cov3D[1], cov3D[2],
+		cov3D[1], cov3D[3], cov3D[4],
+		cov3D[2], cov3D[4], cov3D[5]);
+
+	glm::mat3 T = W * J;
+
+	glm::mat3 cov2D = glm::transpose(T) * glm::transpose(Vrk) * T;
+
+	// Use helper variables for 2D covariance entries. More compact.
+	float a = cov2D[0][0] += 0.3f;
+	float b = cov2D[0][1];
+	float c = cov2D[1][1] += 0.3f;
+
+	float denom = a * c - b * b;
+	float dL_da = 0, dL_db = 0, dL_dc = 0;
+	float denom2inv = 1.0f / ((denom * denom) + 0.0000001f);
+
+	if (denom2inv != 0)
+	{
+		// Gradients of loss w.r.t. entries of 2D covariance matrix,
+		// given gradients of loss w.r.t. conic matrix (inverse covariance matrix).
+		// e.g., dL / da = dL / d_conic_a * d_conic_a / d_a
+		dL_da = denom2inv * (-c * c * dL_dconic.x + 2 * b * c * dL_dconic.y + (denom - a * c) * dL_dconic.z);
+		dL_dc = denom2inv * (-a * a * dL_dconic.z + 2 * a * b * dL_dconic.y + (denom - a * c) * dL_dconic.x);
+		dL_db = denom2inv * 2 * (b * c * dL_dconic.x - (denom + 2 * b * b) * dL_dconic.y + a * b * dL_dconic.z);
+
+		// Gradients of loss L w.r.t. each 3D covariance matrix (Vrk) entry, 
+		// given gradients w.r.t. 2D covariance matrix (diagonal).
+		// cov2D = transpose(T) * transpose(Vrk) * T;
+		dL_dcov[6 * idx + 0] = (T[0][0] * T[0][0] * dL_da + T[0][0] * T[1][0] * dL_db + T[1][0] * T[1][0] * dL_dc);
+		dL_dcov[6 * idx + 3] = (T[0][1] * T[0][1] * dL_da + T[0][1] * T[1][1] * dL_db + T[1][1] * T[1][1] * dL_dc);
+		dL_dcov[6 * idx + 5] = (T[0][2] * T[0][2] * dL_da + T[0][2] * T[1][2] * dL_db + T[1][2] * T[1][2] * dL_dc);
+
+		// Gradients of loss L w.r.t. each 3D covariance matrix (Vrk) entry, 
+		// given gradients w.r.t. 2D covariance matrix (off-diagonal).
+		// Off-diagonal elements appear twice --> double the gradient.
+		// cov2D = transpose(T) * transpose(Vrk) * T;
+		dL_dcov[6 * idx + 1] = 2 * T[0][0] * T[0][1] * dL_da + (T[0][0] * T[1][1] + T[0][1] * T[1][0]) * dL_db + 2 * T[1][0] * T[1][1] * dL_dc;
+		dL_dcov[6 * idx + 2] = 2 * T[0][0] * T[0][2] * dL_da + (T[0][0] * T[1][2] + T[0][2] * T[1][0]) * dL_db + 2 * T[1][0] * T[1][2] * dL_dc;
+		dL_dcov[6 * idx + 4] = 2 * T[0][2] * T[0][1] * dL_da + (T[0][1] * T[1][2] + T[0][2] * T[1][1]) * dL_db + 2 * T[1][1] * T[1][2] * dL_dc;
+	}
+	else
+	{
+		for (int i = 0; i < 6; i++)
+			dL_dcov[6 * idx + i] = 0;
+	}
+
+	// Gradients of loss w.r.t. upper 2x3 portion of intermediate matrix T
+	// cov2D = transpose(T) * transpose(Vrk) * T;
+	float dL_dT00 = 2 * (T[0][0] * Vrk[0][0] + T[0][1] * Vrk[0][1] + T[0][2] * Vrk[0][2]) * dL_da +
+		(T[1][0] * Vrk[0][0] + T[1][1] * Vrk[0][1] + T[1][2] * Vrk[0][2]) * dL_db;
+	float dL_dT01 = 2 * (T[0][0] * Vrk[1][0] + T[0][1] * Vrk[1][1] + T[0][2] * Vrk[1][2]) * dL_da +
+		(T[1][0] * Vrk[1][0] + T[1][1] * Vrk[1][1] + T[1][2] * Vrk[1][2]) * dL_db;
+	float dL_dT02 = 2 * (T[0][0] * Vrk[2][0] + T[0][1] * Vrk[2][1] + T[0][2] * Vrk[2][2]) * dL_da +
+		(T[1][0] * Vrk[2][0] + T[1][1] * Vrk[2][1] + T[1][2] * Vrk[2][2]) * dL_db;
+	float dL_dT10 = 2 * (T[1][0] * Vrk[0][0] + T[1][1] * Vrk[0][1] + T[1][2] * Vrk[0][2]) * dL_dc +
+		(T[0][0] * Vrk[0][0] + T[0][1] * Vrk[0][1] + T[0][2] * Vrk[0][2]) * dL_db;
+	float dL_dT11 = 2 * (T[1][0] * Vrk[1][0] + T[1][1] * Vrk[1][1] + T[1][2] * Vrk[1][2]) * dL_dc +
+		(T[0][0] * Vrk[1][0] + T[0][1] * Vrk[1][1] + T[0][2] * Vrk[1][2]) * dL_db;
+	float dL_dT12 = 2 * (T[1][0] * Vrk[2][0] + T[1][1] * Vrk[2][1] + T[1][2] * Vrk[2][2]) * dL_dc +
+		(T[0][0] * Vrk[2][0] + T[0][1] * Vrk[2][1] + T[0][2] * Vrk[2][2]) * dL_db;
+
+	// Gradients of loss w.r.t. upper 3x2 non-zero entries of Jacobian matrix
+	// T = W * J
+	float dL_dJ00 = W[0][0] * dL_dT00 + W[0][1] * dL_dT01 + W[0][2] * dL_dT02;
+	float dL_dJ02 = W[2][0] * dL_dT00 + W[2][1] * dL_dT01 + W[2][2] * dL_dT02;
+	float dL_dJ11 = W[1][0] * dL_dT10 + W[1][1] * dL_dT11 + W[1][2] * dL_dT12;
+	float dL_dJ12 = W[2][0] * dL_dT10 + W[2][1] * dL_dT11 + W[2][2] * dL_dT12;
+
+	float tz = 1.f / t.z;
+	float tz2 = tz * tz;
+	float tz3 = tz2 * tz;
+
+	// Gradients of loss w.r.t. transformed Gaussian mean t
+	float dL_dtx = x_grad_mul * -h_x * tz2 * dL_dJ02;
+	float dL_dty = y_grad_mul * -h_y * tz2 * dL_dJ12;
+	float dL_dtz = -h_x * tz2 * dL_dJ00 - h_y * tz2 * dL_dJ11 + (2 * h_x * t.x) * tz3 * dL_dJ02 + (2 * h_y * t.y) * tz3 * dL_dJ12;
+
+	// Account for transformation of mean to t
+	// t = transformPoint4x3(mean, view_matrix);
+	float3 dL_dmean = transformVec4x3Transpose({ dL_dtx, dL_dty, dL_dtz }, view_matrix);
+
+	// Gradients of loss w.r.t. Gaussian means, but only the portion 
+	// that is caused because the mean affects the covariance matrix.
+	// Additional mean gradient is accumulated in BACKWARD::preprocess.
+	dL_dmeans[idx] = dL_dmean;
+}
+
+// Backward pass for the conversion of scale and rotation to a 
+// 3D covariance matrix for each Gaussian. 
+__device__ void computeCov3D(int idx, const glm::vec3 scale, float mod, const glm::vec4 rot, const float* dL_dcov3Ds, glm::vec3* dL_dscales, glm::vec4* dL_drots)
+{
+	// Recompute (intermediate) results for the 3D covariance computation.
+	glm::vec4 q = rot;// / glm::length(rot);
+	float r = q.x;
+	float x = q.y;
+	float y = q.z;
+	float z = q.w;
+
+	glm::mat3 R = glm::mat3(
+		1.f - 2.f * (y * y + z * z), 2.f * (x * y - r * z), 2.f * (x * z + r * y),
+		2.f * (x * y + r * z), 1.f - 2.f * (x * x + z * z), 2.f * (y * z - r * x),
+		2.f * (x * z - r * y), 2.f * (y * z + r * x), 1.f - 2.f * (x * x + y * y)
+	);
+
+	glm::mat3 S = glm::mat3(1.0f);
+
+	glm::vec3 s = mod * scale;
+	S[0][0] = s.x;
+	S[1][1] = s.y;
+	S[2][2] = s.z;
+
+	glm::mat3 M = S * R;
+
+	const float* dL_dcov3D = dL_dcov3Ds + 6 * idx;
+
+	glm::vec3 dunc(dL_dcov3D[0], dL_dcov3D[3], dL_dcov3D[5]);
+	glm::vec3 ounc = 0.5f * glm::vec3(dL_dcov3D[1], dL_dcov3D[2], dL_dcov3D[4]);
+
+	// Convert per-element covariance loss gradients to matrix form
+	glm::mat3 dL_dSigma = glm::mat3(
+		dL_dcov3D[0], 0.5f * dL_dcov3D[1], 0.5f * dL_dcov3D[2],
+		0.5f * dL_dcov3D[1], dL_dcov3D[3], 0.5f * dL_dcov3D[4],
+		0.5f * dL_dcov3D[2], 0.5f * dL_dcov3D[4], dL_dcov3D[5]
+	);
+
+	// Compute loss gradient w.r.t. matrix M
+	// dSigma_dM = 2 * M
+	glm::mat3 dL_dM = 2.0f * M * dL_dSigma;
+
+	glm::mat3 Rt = glm::transpose(R);
+	glm::mat3 dL_dMt = glm::transpose(dL_dM);
+
+	// Gradients of loss w.r.t. scale
+	glm::vec3* dL_dscale = dL_dscales + idx;
+	dL_dscale->x = glm::dot(Rt[0], dL_dMt[0]);
+	dL_dscale->y = glm::dot(Rt[1], dL_dMt[1]);
+	dL_dscale->z = glm::dot(Rt[2], dL_dMt[2]);
+
+	dL_dMt[0] *= s.x;
+	dL_dMt[1] *= s.y;
+	dL_dMt[2] *= s.z;
+
+	// Gradients of loss w.r.t. normalized quaternion
+	glm::vec4 dL_dq;
+	dL_dq.x = 2 * z * (dL_dMt[0][1] - dL_dMt[1][0]) + 2 * y * (dL_dMt[2][0] - dL_dMt[0][2]) + 2 * x * (dL_dMt[1][2] - dL_dMt[2][1]);
+	dL_dq.y = 2 * y * (dL_dMt[1][0] + dL_dMt[0][1]) + 2 * z * (dL_dMt[2][0] + dL_dMt[0][2]) + 2 * r * (dL_dMt[1][2] - dL_dMt[2][1]) - 4 * x * (dL_dMt[2][2] + dL_dMt[1][1]);
+	dL_dq.z = 2 * x * (dL_dMt[1][0] + dL_dMt[0][1]) + 2 * r * (dL_dMt[2][0] - dL_dMt[0][2]) + 2 * z * (dL_dMt[1][2] + dL_dMt[2][1]) - 4 * y * (dL_dMt[2][2] + dL_dMt[0][0]);
+	dL_dq.w = 2 * r * (dL_dMt[0][1] - dL_dMt[1][0]) + 2 * x * (dL_dMt[2][0] + dL_dMt[0][2]) + 2 * y * (dL_dMt[1][2] + dL_dMt[2][1]) - 4 * z * (dL_dMt[1][1] + dL_dMt[0][0]);
+
+	// Gradients of loss w.r.t. unnormalized quaternion
+	float4* dL_drot = (float4*)(dL_drots + idx);
+	*dL_drot = float4{ dL_dq.x, dL_dq.y, dL_dq.z, dL_dq.w };//dnormvdv(float4{ rot.x, rot.y, rot.z, rot.w }, float4{ dL_dq.x, dL_dq.y, dL_dq.z, dL_dq.w });
+}
+
+// Backward pass of the preprocessing steps, except
+// for the covariance computation and inversion
+// (those are handled by a previous kernel call)
+template<int C>
+__global__ void preprocessCUDA(
+	int P, int D, int M,
+	const float3* means,
+	const int* radii,
+	const float* shs,
+	const bool* clamped,
+	const glm::vec3* scales,
+	const glm::vec4* rotations,
+	const float scale_modifier,
+	const float* proj,
+	const glm::vec3* campos,
+	const float3* dL_dmean2D,
+	glm::vec3* dL_dmeans,
+	float* dL_dcolor,
+	float* dL_dcov3D,
+	float* dL_dsh,
+	glm::vec3* dL_dscale,
+	glm::vec4* dL_drot)
+{
+	auto idx = cg::this_grid().thread_rank();
+	if (idx >= P || !(radii[idx] > 0))
+		return;
+
+	float3 m = means[idx];
+
+	// Taking care of gradients from the screenspace points
+	float4 m_hom = transformPoint4x4(m, proj);
+	float m_w = 1.0f / (m_hom.w + 0.0000001f);
+
+	// Compute loss gradient w.r.t. 3D means due to gradients of 2D means
+	// from rendering procedure
+	glm::vec3 dL_dmean;
+	float mul1 = (proj[0] * m.x + proj[4] * m.y + proj[8] * m.z + proj[12]) * m_w * m_w;
+	float mul2 = (proj[1] * m.x + proj[5] * m.y + proj[9] * m.z + proj[13]) * m_w * m_w;
+	dL_dmean.x = (proj[0] * m_w - proj[3] * mul1) * dL_dmean2D[idx].x + (proj[1] * m_w - proj[3] * mul2) * dL_dmean2D[idx].y;
+	dL_dmean.y = (proj[4] * m_w - proj[7] * mul1) * dL_dmean2D[idx].x + (proj[5] * m_w - proj[7] * mul2) * dL_dmean2D[idx].y;
+	dL_dmean.z = (proj[8] * m_w - proj[11] * mul1) * dL_dmean2D[idx].x + (proj[9] * m_w - proj[11] * mul2) * dL_dmean2D[idx].y;
+
+	// That's the second part of the mean gradient. Previous computation
+	// of cov2D and following SH conversion also affects it.
+	dL_dmeans[idx] += dL_dmean;
+
+	// Compute gradient updates due to computing colors from SHs
+	if (shs)
+		computeColorFromSH(idx, D, M, (glm::vec3*)means, *campos, shs, clamped, (glm::vec3*)dL_dcolor, (glm::vec3*)dL_dmeans, (glm::vec3*)dL_dsh);
+
+	// Compute gradient updates due to computing covariance from scale/rotation
+	if (scales)
+		computeCov3D(idx, scales[idx], scale_modifier, rotations[idx], dL_dcov3D, dL_dscale, dL_drot);
+}
+
+// Backward version of the rendering procedure.
+template <uint32_t C>
+__global__ void __launch_bounds__(BLOCK_X * BLOCK_Y)
+renderCUDA(
+	const uint2* __restrict__ ranges,
+	const uint32_t* __restrict__ point_list,
+	int W, int H,
+	const float* __restrict__ bg_color,
+	const float2* __restrict__ points_xy_image,
+	const float4* __restrict__ conic_opacity,
+	const float3* __restrict__ points_xyz,
+	const float* __restrict__ colors,
+	const float* __restrict__ depths,
+	const float* __restrict__ projmatrix,
+	const float* __restrict__ final_Ts,
+	const uint32_t* __restrict__ n_contrib,
+	const float* __restrict__ dL_dpixels,
+	const float* __restrict__ dL_depths,
+	float3* __restrict__ dL_dmean2D,
+	float4* __restrict__ dL_dconic2D,
+	float3* __restrict__ dL_dmean3D,
+	float* __restrict__ dL_dopacity,
+	float* __restrict__ dL_dcolors)
+{
+	// We rasterize again. Compute necessary block info.
+	auto block = cg::this_thread_block();
+	const uint32_t horizontal_blocks = (W + BLOCK_X - 1) / BLOCK_X;
+	const uint2 pix_min = { block.group_index().x * BLOCK_X, block.group_index().y * BLOCK_Y };
+	const uint2 pix_max = { min(pix_min.x + BLOCK_X, W), min(pix_min.y + BLOCK_Y , H) };
+	const uint2 pix = { pix_min.x + block.thread_index().x, pix_min.y + block.thread_index().y };
+	const uint32_t pix_id = W * pix.y + pix.x;
+	const float2 pixf = { (float)pix.x, (float)pix.y };
+
+	const bool inside = pix.x < W&& pix.y < H;
+	const uint2 range = ranges[block.group_index().y * horizontal_blocks + block.group_index().x];
+
+	const int rounds = ((range.y - range.x + BLOCK_SIZE - 1) / BLOCK_SIZE);
+
+	bool done = !inside;
+	int toDo = range.y - range.x;
+
+	__shared__ int collected_id[BLOCK_SIZE];
+	__shared__ float2 collected_xy[BLOCK_SIZE];
+	__shared__ float4 collected_conic_opacity[BLOCK_SIZE];
+	__shared__ float collected_colors[C * BLOCK_SIZE];
+	__shared__ float collected_depths[BLOCK_SIZE];
+
+	// In the forward, we stored the final value for T, the
+	// product of all (1 - alpha) factors. 
+	const float T_final = inside ? final_Ts[pix_id] : 0;
+	float T = T_final;
+
+	// We start from the back. The ID of the last contributing
+	// Gaussian is known from each pixel from the forward.
+	uint32_t contributor = toDo;
+	const int last_contributor = inside ? n_contrib[pix_id] : 0;
+
+	float accum_rec[C] = { 0 };
+	float dL_dpixel[C];
+	float dL_depth;
+	float accum_depth_rec = 0;
+	if (inside)
+	{
+		for (int i = 0; i < C; i++)
+			dL_dpixel[i] = dL_dpixels[i * H * W + pix_id];
+	        dL_depth = dL_depths[pix_id];
+	}
+
+	float last_alpha = 0;
+	float last_color[C] = { 0 };
+	float last_depth = 0;
+
+	// Gradient of pixel coordinate w.r.t. normalized 
+	// screen-space viewport corrdinates (-1 to 1)
+	const float ddelx_dx = 0.5 * W;
+	const float ddely_dy = 0.5 * H;
+
+	// Traverse all Gaussians
+	for (int i = 0; i < rounds; i++, toDo -= BLOCK_SIZE)
+	{
+		// Load auxiliary data into shared memory, start in the BACK
+		// and load them in revers order.
+		block.sync();
+		const int progress = i * BLOCK_SIZE + block.thread_rank();
+		if (range.x + progress < range.y)
+		{
+			const int coll_id = point_list[range.y - progress - 1];
+			collected_id[block.thread_rank()] = coll_id;
+			collected_xy[block.thread_rank()] = points_xy_image[coll_id];
+			collected_conic_opacity[block.thread_rank()] = conic_opacity[coll_id];
+			for (int i = 0; i < C; i++)
+				collected_colors[i * BLOCK_SIZE + block.thread_rank()] = colors[coll_id * C + i];
+		        collected_depths[block.thread_rank()] = depths[coll_id];
+		}
+		block.sync();
+
+		// Iterate over Gaussians
+		for (int j = 0; !done && j < min(BLOCK_SIZE, toDo); j++)
+		{
+			// Keep track of current Gaussian ID. Skip, if this one
+			// is behind the last contributor for this pixel.
+			contributor--;
+			if (contributor >= last_contributor)
+				continue;
+
+			// Compute blending values, as before.
+			const float2 xy = collected_xy[j];
+			const float2 d = { xy.x - pixf.x, xy.y - pixf.y };
+			const float4 con_o = collected_conic_opacity[j];
+			const float power = -0.5f * (con_o.x * d.x * d.x + con_o.z * d.y * d.y) - con_o.y * d.x * d.y;
+			if (power > 0.0f)
+				continue;
+
+			const float G = exp(power);
+			const float alpha = min(0.99f, con_o.w * G);
+			if (alpha < 1.0f / 255.0f)
+				continue;
+
+			T = T / (1.f - alpha);
+			const float dchannel_dcolor = alpha * T;
+
+			// Propagate gradients to per-Gaussian colors and keep
+			// gradients w.r.t. alpha (blending factor for a Gaussian/pixel
+			// pair).
+			float dL_dalpha = 0.0f;
+			const int global_id = collected_id[j];
+			for (int ch = 0; ch < C; ch++)
+			{
+				const float c = collected_colors[ch * BLOCK_SIZE + j];
+				// Update last color (to be used in the next iteration)
+				accum_rec[ch] = last_alpha * last_color[ch] + (1.f - last_alpha) * accum_rec[ch];
+				last_color[ch] = c;
+
+				const float dL_dchannel = dL_dpixel[ch];
+				dL_dalpha += (c - accum_rec[ch]) * dL_dchannel;
+				// Update the gradients w.r.t. color of the Gaussian. 
+				// Atomic, since this pixel is just one of potentially
+				// many that were affected by this Gaussian.
+				atomicAdd(&(dL_dcolors[global_id * C + ch]), dchannel_dcolor * dL_dchannel);
+			}
+			const float c_d = collected_depths[j];
+			accum_depth_rec = last_alpha * last_depth + (1.f - last_alpha) * accum_depth_rec;
+			last_depth = c_d;
+			dL_dalpha += (c_d - accum_depth_rec) * dL_depth;
+			dL_dalpha *= T;
+
+			// Update the gradients w.r.t. depth (=z in camera coord.) of the Gaussian.
+			float3 m = points_xyz[global_id];
+			float4 m_hom = transformPoint4x4(m, projmatrix);
+			float m_w = 1.0f / (m_hom.w + 0.0000001f);
+			float mul3 = (projmatrix[2] * m.x + projmatrix[6] * m.y + projmatrix[10] * m.z + projmatrix[14]) * m_w * m_w;
+			// Update gradients w.r.t. 2D mean position of the Gaussian
+			const float dL_camz = dchannel_dcolor * dL_depth;
+			atomicAdd(&dL_dmean3D[global_id].x, (projmatrix[2] * m_w - projmatrix[3] * mul3) * dL_camz);
+			atomicAdd(&dL_dmean3D[global_id].y, (projmatrix[6] * m_w - projmatrix[7] * mul3) * dL_camz);
+			atomicAdd(&dL_dmean3D[global_id].z, (projmatrix[10] * m_w - projmatrix[11] * mul3) * dL_camz);
+			// Update last alpha (to be used in the next iteration)
+			last_alpha = alpha;
+
+			// Account for fact that alpha also influences how much of
+			// the background color is added if nothing left to blend
+			float bg_dot_dpixel = 0;
+			for (int i = 0; i < C; i++)
+				bg_dot_dpixel += bg_color[i] * dL_dpixel[i];
+			dL_dalpha += (-T_final / (1.f - alpha)) * bg_dot_dpixel;
+
+
+			// Helpful reusable temporary variables
+			const float dL_dG = con_o.w * dL_dalpha;
+			const float gdx = G * d.x;
+			const float gdy = G * d.y;
+			const float dG_ddelx = -gdx * con_o.x - gdy * con_o.y;
+			const float dG_ddely = -gdy * con_o.z - gdx * con_o.y;
+
+			// Update gradients w.r.t. 2D mean position of the Gaussian
+			atomicAdd(&dL_dmean2D[global_id].x, dL_dG * dG_ddelx * ddelx_dx);
+			atomicAdd(&dL_dmean2D[global_id].y, dL_dG * dG_ddely * ddely_dy);
+
+			// Update gradients w.r.t. 2D covariance (2x2 matrix, symmetric)
+			atomicAdd(&dL_dconic2D[global_id].x, -0.5f * gdx * d.x * dL_dG);
+			atomicAdd(&dL_dconic2D[global_id].y, -0.5f * gdx * d.y * dL_dG);
+			atomicAdd(&dL_dconic2D[global_id].w, -0.5f * gdy * d.y * dL_dG);
+
+			// Update gradients w.r.t. opacity of the Gaussian
+			atomicAdd(&(dL_dopacity[global_id]), G * dL_dalpha);
+		}
+	}
+}
+
+void BACKWARD::preprocess(
+	int P, int D, int M,
+	const float3* means3D,
+	const int* radii,
+	const float* shs,
+	const bool* clamped,
+	const glm::vec3* scales,
+	const glm::vec4* rotations,
+	const float scale_modifier,
+	const float* cov3Ds,
+	const float* viewmatrix,
+	const float* projmatrix,
+	const float focal_x, float focal_y,
+	const float tan_fovx, float tan_fovy,
+	const glm::vec3* campos,
+	const float3* dL_dmean2D,
+	const float* dL_dconic,
+	glm::vec3* dL_dmean3D,
+	float* dL_dcolor,
+	float* dL_dcov3D,
+	float* dL_dsh,
+	glm::vec3* dL_dscale,
+	glm::vec4* dL_drot)
+{
+	// Propagate gradients for the path of 2D conic matrix computation. 
+	// Somewhat long, thus it is its own kernel rather than being part of 
+	// "preprocess". When done, loss gradient w.r.t. 3D means has been
+	// modified and gradient w.r.t. 3D covariance matrix has been computed.	
+	computeCov2DCUDA << <(P + 255) / 256, 256 >> > (
+		P,
+		means3D,
+		radii,
+		cov3Ds,
+		focal_x,
+		focal_y,
+		tan_fovx,
+		tan_fovy,
+		viewmatrix,
+		dL_dconic,
+		(float3*)dL_dmean3D,
+		dL_dcov3D);
+
+	// Propagate gradients for remaining steps: finish 3D mean gradients,
+	// propagate color gradients to SH (if desireD), propagate 3D covariance
+	// matrix gradients to scale and rotation.
+	preprocessCUDA<NUM_CHANNELS> << < (P + 255) / 256, 256 >> > (
+		P, D, M,
+		(float3*)means3D,
+		radii,
+		shs,
+		clamped,
+		(glm::vec3*)scales,
+		(glm::vec4*)rotations,
+		scale_modifier,
+		projmatrix,
+		campos,
+		(float3*)dL_dmean2D,
+		(glm::vec3*)dL_dmean3D,
+		dL_dcolor,
+		dL_dcov3D,
+		dL_dsh,
+		dL_dscale,
+		dL_drot);
+}
+
+void BACKWARD::render(
+	const dim3 grid, const dim3 block,
+	const uint2* ranges,
+	const uint32_t* point_list,
+	int W, int H,
+	const float* bg_color,
+	const float2* means2D,
+	const float4* conic_opacity,
+	const float3* means3D,
+	const float* colors,
+	const float* depths,
+	const float* projmatrix,
+	const float* final_Ts,
+	const uint32_t* n_contrib,
+	const float* dL_dpixels,
+	const float* dL_depths,
+	float3* dL_dmean2D,
+	float4* dL_dconic2D,
+	float3* dL_dmean3D,
+	float* dL_dopacity,
+	float* dL_dcolors)
+{
+	renderCUDA<NUM_CHANNELS> << <grid, block >> >(
+		ranges,
+		point_list,
+		W, H,
+		bg_color,
+		means2D,
+		conic_opacity,
+		means3D,
+		colors,
+		depths,
+		projmatrix,
+		final_Ts,
+		n_contrib,
+		dL_dpixels,
+		dL_depths,
+		dL_dmean2D,
+		dL_dconic2D,
+		dL_dmean3D,
+		dL_dopacity,
+		dL_dcolors
+		);
+}

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/backward.h

@@ -0,0 +1,70 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#ifndef CUDA_RASTERIZER_BACKWARD_H_INCLUDED
+#define CUDA_RASTERIZER_BACKWARD_H_INCLUDED
+
+#include <cuda.h>
+#include "cuda_runtime.h"
+#include "device_launch_parameters.h"
+#define GLM_FORCE_CUDA
+#include <glm/glm.hpp>
+
+namespace BACKWARD
+{
+	void render(
+		const dim3 grid, dim3 block,
+		const uint2* ranges,
+		const uint32_t* point_list,
+		int W, int H,
+		const float* bg_color,
+		const float2* means2D,
+		const float4* conic_opacity,
+		const float3* means3D,
+		const float* colors,
+		const float* depths,
+		const float* projmatrix,
+		const float* final_Ts,
+		const uint32_t* n_contrib,
+		const float* dL_dpixels,
+		const float* dL_depths,
+		float3* dL_dmean2D,
+		float4* dL_dconic2D,
+		float3* dL_dmean3D,
+		float* dL_dopacity,
+		float* dL_dcolors);
+
+	void preprocess(
+		int P, int D, int M,
+		const float3* means,
+		const int* radii,
+		const float* shs,
+		const bool* clamped,
+		const glm::vec3* scales,
+		const glm::vec4* rotations,
+		const float scale_modifier,
+		const float* cov3Ds,
+		const float* view,
+		const float* proj,
+		const float focal_x, float focal_y,
+		const float tan_fovx, float tan_fovy,
+		const glm::vec3* campos,
+		const float3* dL_dmean2D,
+		const float* dL_dconics,
+		glm::vec3* dL_dmeans,
+		float* dL_dcolor,
+		float* dL_dcov3D,
+		float* dL_dsh,
+		glm::vec3* dL_dscale,
+		glm::vec4* dL_drot);
+}
+
+#endif

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/config.h

@@ -0,0 +1,19 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#ifndef CUDA_RASTERIZER_CONFIG_H_INCLUDED
+#define CUDA_RASTERIZER_CONFIG_H_INCLUDED
+
+#define NUM_CHANNELS 3 // Default 3, RGB
+#define BLOCK_X 16
+#define BLOCK_Y 16
+
+#endif

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/forward.cu

@@ -0,0 +1,476 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#include "forward.h"
+#include "auxiliary.h"
+#include <cooperative_groups.h>
+#include <cooperative_groups/reduce.h>
+namespace cg = cooperative_groups;
+
+// Forward method for converting the input spherical harmonics
+// coefficients of each Gaussian to a simple RGB color.
+__device__ glm::vec3 computeColorFromSH(int idx, int deg, int max_coeffs, const glm::vec3* means, glm::vec3 campos, const float* shs, bool* clamped)
+{
+	// The implementation is loosely based on code for 
+	// "Differentiable Point-Based Radiance Fields for 
+	// Efficient View Synthesis" by Zhang et al. (2022)
+	glm::vec3 pos = means[idx];
+	glm::vec3 dir = pos - campos;
+	dir = dir / glm::length(dir);
+
+	glm::vec3* sh = ((glm::vec3*)shs) + idx * max_coeffs;
+	glm::vec3 result = SH_C0 * sh[0];
+
+	if (deg > 0)
+	{
+		float x = dir.x;
+		float y = dir.y;
+		float z = dir.z;
+		result = result - SH_C1 * y * sh[1] + SH_C1 * z * sh[2] - SH_C1 * x * sh[3];
+
+		if (deg > 1)
+		{
+			float xx = x * x, yy = y * y, zz = z * z;
+			float xy = x * y, yz = y * z, xz = x * z;
+			result = result +
+				SH_C2[0] * xy * sh[4] +
+				SH_C2[1] * yz * sh[5] +
+				SH_C2[2] * (2.0f * zz - xx - yy) * sh[6] +
+				SH_C2[3] * xz * sh[7] +
+				SH_C2[4] * (xx - yy) * sh[8];
+
+			if (deg > 2)
+			{
+				result = result +
+					SH_C3[0] * y * (3.0f * xx - yy) * sh[9] +
+					SH_C3[1] * xy * z * sh[10] +
+					SH_C3[2] * y * (4.0f * zz - xx - yy) * sh[11] +
+					SH_C3[3] * z * (2.0f * zz - 3.0f * xx - 3.0f * yy) * sh[12] +
+					SH_C3[4] * x * (4.0f * zz - xx - yy) * sh[13] +
+					SH_C3[5] * z * (xx - yy) * sh[14] +
+					SH_C3[6] * x * (xx - 3.0f * yy) * sh[15];
+			}
+		}
+	}
+	result += 0.5f;
+
+	// RGB colors are clamped to positive values. If values are
+	// clamped, we need to keep track of this for the backward pass.
+	clamped[3 * idx + 0] = (result.x < 0);
+	clamped[3 * idx + 1] = (result.y < 0);
+	clamped[3 * idx + 2] = (result.z < 0);
+	return glm::max(result, 0.0f);
+}
+
+// Forward version of 2D covariance matrix computation
+__device__ float3 computeCov2D(const float3& mean, float focal_x, float focal_y, float tan_fovx, float tan_fovy, const float* cov3D, const float* viewmatrix)
+{
+	// The following models the steps outlined by equations 29
+	// and 31 in "EWA Splatting" (Zwicker et al., 2002). 
+	// Additionally considers aspect / scaling of viewport.
+	// Transposes used to account for row-/column-major conventions.
+	float3 t = transformPoint4x3(mean, viewmatrix);
+
+	const float limx = 1.3f * tan_fovx;
+	const float limy = 1.3f * tan_fovy;
+	const float txtz = t.x / t.z;
+	const float tytz = t.y / t.z;
+	t.x = min(limx, max(-limx, txtz)) * t.z;
+	t.y = min(limy, max(-limy, tytz)) * t.z;
+
+	glm::mat3 J = glm::mat3(
+		focal_x / t.z, 0.0f, -(focal_x * t.x) / (t.z * t.z),
+		0.0f, focal_y / t.z, -(focal_y * t.y) / (t.z * t.z),
+		0, 0, 0);
+
+	glm::mat3 W = glm::mat3(
+		viewmatrix[0], viewmatrix[4], viewmatrix[8],
+		viewmatrix[1], viewmatrix[5], viewmatrix[9],
+		viewmatrix[2], viewmatrix[6], viewmatrix[10]);
+
+	glm::mat3 T = W * J;
+
+	glm::mat3 Vrk = glm::mat3(
+		cov3D[0], cov3D[1], cov3D[2],
+		cov3D[1], cov3D[3], cov3D[4],
+		cov3D[2], cov3D[4], cov3D[5]);
+
+	glm::mat3 cov = glm::transpose(T) * glm::transpose(Vrk) * T;
+
+	// Apply low-pass filter: every Gaussian should be at least
+	// one pixel wide/high. Discard 3rd row and column.
+	cov[0][0] += 0.3f;
+	cov[1][1] += 0.3f;
+	return { float(cov[0][0]), float(cov[0][1]), float(cov[1][1]) };
+}
+
+// Forward method for converting scale and rotation properties of each
+// Gaussian to a 3D covariance matrix in world space. Also takes care
+// of quaternion normalization.
+__device__ void computeCov3D(const glm::vec3 scale, float mod, const glm::vec4 rot, float* cov3D)
+{
+	// Create scaling matrix
+	glm::mat3 S = glm::mat3(1.0f);
+	S[0][0] = mod * scale.x;
+	S[1][1] = mod * scale.y;
+	S[2][2] = mod * scale.z;
+
+	// Normalize quaternion to get valid rotation
+	glm::vec4 q = rot;// / glm::length(rot);
+	float r = q.x;
+	float x = q.y;
+	float y = q.z;
+	float z = q.w;
+
+	// Compute rotation matrix from quaternion
+	glm::mat3 R = glm::mat3(
+		1.f - 2.f * (y * y + z * z), 2.f * (x * y - r * z), 2.f * (x * z + r * y),
+		2.f * (x * y + r * z), 1.f - 2.f * (x * x + z * z), 2.f * (y * z - r * x),
+		2.f * (x * z - r * y), 2.f * (y * z + r * x), 1.f - 2.f * (x * x + y * y)
+	);
+
+	glm::mat3 M = S * R;
+
+	// Compute 3D world covariance matrix Sigma
+	glm::mat3 Sigma = glm::transpose(M) * M;
+
+	// Covariance is symmetric, only store upper right
+	cov3D[0] = Sigma[0][0];
+	cov3D[1] = Sigma[0][1];
+	cov3D[2] = Sigma[0][2];
+	cov3D[3] = Sigma[1][1];
+	cov3D[4] = Sigma[1][2];
+	cov3D[5] = Sigma[2][2];
+}
+
+// Perform initial steps for each Gaussian prior to rasterization.
+template<int C>
+__global__ void preprocessCUDA(int P, int D, int M,
+	const float* orig_points,
+	const glm::vec3* scales,
+	const float scale_modifier,
+	const glm::vec4* rotations,
+	const float* opacities,
+	const float* shs,
+	bool* clamped,
+	const float* cov3D_precomp,
+	const float* colors_precomp,
+	const float* viewmatrix,
+	const float* projmatrix,
+	const glm::vec3* cam_pos,
+	const int W, int H,
+	const float tan_fovx, float tan_fovy,
+	const float focal_x, float focal_y,
+	int* radii,
+	float2* points_xy_image,
+	float* depths,
+	float* cov3Ds,
+	float* rgb,
+	float4* conic_opacity,
+	const dim3 grid,
+	uint32_t* tiles_touched,
+	bool prefiltered)
+{
+	auto idx = cg::this_grid().thread_rank();
+	if (idx >= P)
+		return;
+
+	// Initialize radius and touched tiles to 0. If this isn't changed,
+	// this Gaussian will not be processed further.
+	radii[idx] = 0;
+	tiles_touched[idx] = 0;
+
+	// Perform near culling, quit if outside.
+	float3 p_view;
+	if (!in_frustum(idx, orig_points, viewmatrix, projmatrix, prefiltered, p_view))
+		return;
+
+	// Transform point by projecting
+	float3 p_orig = { orig_points[3 * idx], orig_points[3 * idx + 1], orig_points[3 * idx + 2] };
+	float4 p_hom = transformPoint4x4(p_orig, projmatrix);
+	float p_w = 1.0f / (p_hom.w + 0.0000001f);
+	float3 p_proj = { p_hom.x * p_w, p_hom.y * p_w, p_hom.z * p_w };
+
+	// If 3D covariance matrix is precomputed, use it, otherwise compute
+	// from scaling and rotation parameters. 
+	const float* cov3D;
+	if (cov3D_precomp != nullptr)
+	{
+		cov3D = cov3D_precomp + idx * 6;
+	}
+	else
+	{
+		computeCov3D(scales[idx], scale_modifier, rotations[idx], cov3Ds + idx * 6);
+		cov3D = cov3Ds + idx * 6;
+	}
+
+	// Compute 2D screen-space covariance matrix
+	float3 cov = computeCov2D(p_orig, focal_x, focal_y, tan_fovx, tan_fovy, cov3D, viewmatrix);
+
+	// Invert covariance (EWA algorithm)
+	float det = (cov.x * cov.z - cov.y * cov.y);
+	if (det == 0.0f)
+		return;
+	float det_inv = 1.f / det;
+	float3 conic = { cov.z * det_inv, -cov.y * det_inv, cov.x * det_inv };
+
+	// Compute extent in screen space (by finding eigenvalues of
+	// 2D covariance matrix). Use extent to compute a bounding rectangle
+	// of screen-space tiles that this Gaussian overlaps with. Quit if
+	// rectangle covers 0 tiles. 
+	float mid = 0.5f * (cov.x + cov.z);
+	float lambda1 = mid + sqrt(max(0.1f, mid * mid - det));
+	float lambda2 = mid - sqrt(max(0.1f, mid * mid - det));
+	float my_radius = ceil(3.f * sqrt(max(lambda1, lambda2)));
+	float2 point_image = { ndc2Pix(p_proj.x, W), ndc2Pix(p_proj.y, H) };
+	uint2 rect_min, rect_max;
+	getRect(point_image, my_radius, rect_min, rect_max, grid);
+	if ((rect_max.x - rect_min.x) * (rect_max.y - rect_min.y) == 0)
+		return;
+
+	// If colors have been precomputed, use them, otherwise convert
+	// spherical harmonics coefficients to RGB color.
+	if (colors_precomp == nullptr)
+	{
+		glm::vec3 result = computeColorFromSH(idx, D, M, (glm::vec3*)orig_points, *cam_pos, shs, clamped);
+		rgb[idx * C + 0] = result.x;
+		rgb[idx * C + 1] = result.y;
+		rgb[idx * C + 2] = result.z;
+	}
+
+	// Store some useful helper data for the next steps.
+	depths[idx] = p_view.z;
+	radii[idx] = my_radius;
+	points_xy_image[idx] = point_image;
+	// Inverse 2D covariance and opacity neatly pack into one float4
+	conic_opacity[idx] = { conic.x, conic.y, conic.z, opacities[idx] };
+	tiles_touched[idx] = (rect_max.y - rect_min.y) * (rect_max.x - rect_min.x);
+}
+
+// Main rasterization method. Collaboratively works on one tile per
+// block, each thread treats one pixel. Alternates between fetching 
+// and rasterizing data.
+template <uint32_t CHANNELS>
+__global__ void __launch_bounds__(BLOCK_X * BLOCK_Y)
+renderCUDA(
+	const uint2* __restrict__ ranges,
+	const uint32_t* __restrict__ point_list,
+	int W, int H,
+	const float2* __restrict__ points_xy_image,
+	const float* __restrict__ features,
+	const float* __restrict__ depths,
+	const float4* __restrict__ conic_opacity,
+	float* __restrict__ final_T,
+	uint32_t* __restrict__ n_contrib,
+	const float* __restrict__ bg_color,
+	float* __restrict__ out_color,
+	float* __restrict__ out_depth)
+{
+	// Identify current tile and associated min/max pixel range.
+	auto block = cg::this_thread_block();
+	uint32_t horizontal_blocks = (W + BLOCK_X - 1) / BLOCK_X;
+	uint2 pix_min = { block.group_index().x * BLOCK_X, block.group_index().y * BLOCK_Y };
+	uint2 pix_max = { min(pix_min.x + BLOCK_X, W), min(pix_min.y + BLOCK_Y , H) };
+	uint2 pix = { pix_min.x + block.thread_index().x, pix_min.y + block.thread_index().y };
+	uint32_t pix_id = W * pix.y + pix.x;
+	float2 pixf = { (float)pix.x, (float)pix.y };
+
+	// Check if this thread is associated with a valid pixel or outside.
+	bool inside = pix.x < W&& pix.y < H;
+	// Done threads can help with fetching, but don't rasterize
+	bool done = !inside;
+
+	// Load start/end range of IDs to process in bit sorted list.
+	uint2 range = ranges[block.group_index().y * horizontal_blocks + block.group_index().x];
+	const int rounds = ((range.y - range.x + BLOCK_SIZE - 1) / BLOCK_SIZE);
+	int toDo = range.y - range.x;
+
+	// Allocate storage for batches of collectively fetched data.
+	__shared__ int collected_id[BLOCK_SIZE];
+	__shared__ float2 collected_xy[BLOCK_SIZE];
+	__shared__ float4 collected_conic_opacity[BLOCK_SIZE];
+
+	// Initialize helper variables
+	float T = 1.0f;
+	uint32_t contributor = 0;
+	uint32_t last_contributor = 0;
+	float C[CHANNELS] = { 0 };
+	float D = { 0 };
+	float acc = { 0.000001f };
+
+	// Iterate over batches until all done or range is complete
+	for (int i = 0; i < rounds; i++, toDo -= BLOCK_SIZE)
+	{
+		// End if entire block votes that it is done rasterizing
+		int num_done = __syncthreads_count(done);
+		if (num_done == BLOCK_SIZE)
+			break;
+
+		// Collectively fetch per-Gaussian data from global to shared
+		int progress = i * BLOCK_SIZE + block.thread_rank();
+		if (range.x + progress < range.y)
+		{
+			int coll_id = point_list[range.x + progress];
+			collected_id[block.thread_rank()] = coll_id;
+			collected_xy[block.thread_rank()] = points_xy_image[coll_id];
+			collected_conic_opacity[block.thread_rank()] = conic_opacity[coll_id];
+		}
+		block.sync();
+
+		// Iterate over current batch
+		for (int j = 0; !done && j < min(BLOCK_SIZE, toDo); j++)
+		{
+			// Keep track of current position in range
+			contributor++;
+
+			// Resample using conic matrix (cf. "Surface 
+			// Splatting" by Zwicker et al., 2001)
+			float2 xy = collected_xy[j];
+			float2 d = { xy.x - pixf.x, xy.y - pixf.y };
+			float4 con_o = collected_conic_opacity[j];
+			float power = -0.5f * (con_o.x * d.x * d.x + con_o.z * d.y * d.y) - con_o.y * d.x * d.y;
+			if (power > 0.0f)
+				continue;
+
+			// Eq. (2) from 3D Gaussian splatting paper.
+			// Obtain alpha by multiplying with Gaussian opacity
+			// and its exponential falloff from mean.
+			// Avoid numerical instabilities (see paper appendix). 
+			float alpha = min(0.99f, con_o.w * exp(power));
+			if (alpha < 1.0f / 255.0f)
+				continue;
+			float test_T = T * (1 - alpha);
+			if (test_T < 0.0001f)
+			{
+				done = true;
+				continue;
+			}
+
+			// Eq. (3) from 3D Gaussian splatting paper.
+			for (int ch = 0; ch < CHANNELS; ch++)
+				C[ch] += features[collected_id[j] * CHANNELS + ch] * alpha * T;
+
+			// if (D < 0.0001f && alpha > 0.05f){
+			// 	D = depths[collected_id[j]];
+			// }
+			D += depths[collected_id[j]] * alpha * T;
+			acc += alpha * T;
+
+			T = test_T;
+
+			// Keep track of last range entry to update this
+			// pixel.
+			last_contributor = contributor;
+		}
+	}
+
+	// All threads that treat valid pixel write out their final
+	// rendering data to the frame and auxiliary buffers.
+	if (inside)
+	{
+		final_T[pix_id] = T;
+		n_contrib[pix_id] = last_contributor;
+		for (int ch = 0; ch < CHANNELS; ch++)
+			out_color[ch * H * W + pix_id] = C[ch] + T * bg_color[ch];
+
+		if (acc > 0.5f){
+			out_depth[pix_id] = D/acc;
+		}else{
+			out_depth[pix_id] = 0;
+		}
+		// out_depth[pix_id] = D;
+	}
+}
+
+void FORWARD::render(
+	const dim3 grid, dim3 block,
+	const uint2* ranges,
+	const uint32_t* point_list,
+	int W, int H,
+	const float2* means2D,
+	const float* colors,
+	const float* depths,
+	const float4* conic_opacity,
+	float* final_T,
+	uint32_t* n_contrib,
+	const float* bg_color,
+	float* out_color,
+	float* out_depth)
+{
+	renderCUDA<NUM_CHANNELS> << <grid, block >> > (
+		ranges,
+		point_list,
+		W, H,
+		means2D,
+		colors,
+		depths,
+		conic_opacity,
+		final_T,
+		n_contrib,
+		bg_color,
+		out_color,
+		out_depth);
+}
+
+void FORWARD::preprocess(int P, int D, int M,
+	const float* means3D,
+	const glm::vec3* scales,
+	const float scale_modifier,
+	const glm::vec4* rotations,
+	const float* opacities,
+	const float* shs,
+	bool* clamped,
+	const float* cov3D_precomp,
+	const float* colors_precomp,
+	const float* viewmatrix,
+	const float* projmatrix,
+	const glm::vec3* cam_pos,
+	const int W, int H,
+	const float focal_x, float focal_y,
+	const float tan_fovx, float tan_fovy,
+	int* radii,
+	float2* means2D,
+	float* depths,
+	float* cov3Ds,
+	float* rgb,
+	float4* conic_opacity,
+	const dim3 grid,
+	uint32_t* tiles_touched,
+	bool prefiltered)
+{
+	preprocessCUDA<NUM_CHANNELS> << <(P + 255) / 256, 256 >> > (
+		P, D, M,
+		means3D,
+		scales,
+		scale_modifier,
+		rotations,
+		opacities,
+		shs,
+		clamped,
+		cov3D_precomp,
+		colors_precomp,
+		viewmatrix, 
+		projmatrix,
+		cam_pos,
+		W, H,
+		tan_fovx, tan_fovy,
+		focal_x, focal_y,
+		radii,
+		means2D,
+		depths,
+		cov3Ds,
+		rgb,
+		conic_opacity,
+		grid,
+		tiles_touched,
+		prefiltered
+		);
+}

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/forward.h

@@ -0,0 +1,68 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#ifndef CUDA_RASTERIZER_FORWARD_H_INCLUDED
+#define CUDA_RASTERIZER_FORWARD_H_INCLUDED
+
+#include <cuda.h>
+#include "cuda_runtime.h"
+#include "device_launch_parameters.h"
+#define GLM_FORCE_CUDA
+#include <glm/glm.hpp>
+
+namespace FORWARD
+{
+	// Perform initial steps for each Gaussian prior to rasterization.
+	void preprocess(int P, int D, int M,
+		const float* orig_points,
+		const glm::vec3* scales,
+		const float scale_modifier,
+		const glm::vec4* rotations,
+		const float* opacities,
+		const float* shs,
+		bool* clamped,
+		const float* cov3D_precomp,
+		const float* colors_precomp,
+		const float* viewmatrix,
+		const float* projmatrix,
+		const glm::vec3* cam_pos,
+		const int W, int H,
+		const float focal_x, float focal_y,
+		const float tan_fovx, float tan_fovy,
+		int* radii,
+		float2* points_xy_image,
+		float* depths,
+		float* cov3Ds,
+		float* colors,
+		float4* conic_opacity,
+		const dim3 grid,
+		uint32_t* tiles_touched,
+		bool prefiltered);
+
+	// Main rasterization method.
+	void render(
+		const dim3 grid, dim3 block,
+		const uint2* ranges,
+		const uint32_t* point_list,
+		int W, int H,
+		const float2* points_xy_image,
+		const float* features,
+		const float* depths,
+		const float4* conic_opacity,
+		float* final_T,
+		uint32_t* n_contrib,
+		const float* bg_color,
+		float* out_color,
+		float* out_depth);
+}
+
+
+#endif

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/rasterizer.h

@@ -0,0 +1,90 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#ifndef CUDA_RASTERIZER_H_INCLUDED
+#define CUDA_RASTERIZER_H_INCLUDED
+
+#include <vector>
+#include <functional>
+
+namespace CudaRasterizer
+{
+	class Rasterizer
+	{
+	public:
+
+		static void markVisible(
+			int P,
+			float* means3D,
+			float* viewmatrix,
+			float* projmatrix,
+			bool* present);
+
+		static int forward(
+			std::function<char* (size_t)> geometryBuffer,
+			std::function<char* (size_t)> binningBuffer,
+			std::function<char* (size_t)> imageBuffer,
+			const int P, int D, int M,
+			const float* background,
+			const int width, int height,
+			const float* means3D,
+			const float* shs,
+			const float* colors_precomp,
+			const float* opacities,
+			const float* scales,
+			const float scale_modifier,
+			const float* rotations,
+			const float* cov3D_precomp,
+			const float* viewmatrix,
+			const float* projmatrix,
+			const float* cam_pos,
+			const float tan_fovx, float tan_fovy,
+			const bool prefiltered,
+			float* out_color,
+			float* out_depth,
+			int* radii = nullptr,
+			bool debug = false);
+
+		static void backward(
+			const int P, int D, int M, int R,
+			const float* background,
+			const int width, int height,
+			const float* means3D,
+			const float* shs,
+			const float* colors_precomp,
+			const float* scales,
+			const float scale_modifier,
+			const float* rotations,
+			const float* cov3D_precomp,
+			const float* viewmatrix,
+			const float* projmatrix,
+			const float* campos,
+			const float tan_fovx, float tan_fovy,
+			const int* radii,
+			char* geom_buffer,
+			char* binning_buffer,
+			char* image_buffer,
+			const float* dL_dpix,
+			const float* dL_depths,
+			float* dL_dmean2D,
+			float* dL_dconic,
+			float* dL_dopacity,
+			float* dL_dcolor,
+			float* dL_dmean3D,
+			float* dL_dcov3D,
+			float* dL_dsh,
+			float* dL_dscale,
+			float* dL_drot,
+			bool debug);
+	};
+};
+
+#endif

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/rasterizer_impl.cu

@@ -0,0 +1,444 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#include "rasterizer_impl.h"
+#include <iostream>
+#include <fstream>
+#include <algorithm>
+#include <numeric>
+#include <cuda.h>
+#include "cuda_runtime.h"
+#include "device_launch_parameters.h"
+#include <cub/cub.cuh>
+#include <cub/device/device_radix_sort.cuh>
+#define GLM_FORCE_CUDA
+#include <glm/glm.hpp>
+
+#include <cooperative_groups.h>
+#include <cooperative_groups/reduce.h>
+namespace cg = cooperative_groups;
+
+#include "auxiliary.h"
+#include "forward.h"
+#include "backward.h"
+
+// Helper function to find the next-highest bit of the MSB
+// on the CPU.
+uint32_t getHigherMsb(uint32_t n)
+{
+	uint32_t msb = sizeof(n) * 4;
+	uint32_t step = msb;
+	while (step > 1)
+	{
+		step /= 2;
+		if (n >> msb)
+			msb += step;
+		else
+			msb -= step;
+	}
+	if (n >> msb)
+		msb++;
+	return msb;
+}
+
+// Wrapper method to call auxiliary coarse frustum containment test.
+// Mark all Gaussians that pass it.
+__global__ void checkFrustum(int P,
+	const float* orig_points,
+	const float* viewmatrix,
+	const float* projmatrix,
+	bool* present)
+{
+	auto idx = cg::this_grid().thread_rank();
+	if (idx >= P)
+		return;
+
+	float3 p_view;
+	present[idx] = in_frustum(idx, orig_points, viewmatrix, projmatrix, false, p_view);
+}
+
+// Generates one key/value pair for all Gaussian / tile overlaps. 
+// Run once per Gaussian (1:N mapping).
+__global__ void duplicateWithKeys(
+	int P,
+	const float2* points_xy,
+	const float* depths,
+	const uint32_t* offsets,
+	uint64_t* gaussian_keys_unsorted,
+	uint32_t* gaussian_values_unsorted,
+	int* radii,
+	dim3 grid)
+{
+	auto idx = cg::this_grid().thread_rank();
+	if (idx >= P)
+		return;
+
+	// Generate no key/value pair for invisible Gaussians
+	if (radii[idx] > 0)
+	{
+		// Find this Gaussian's offset in buffer for writing keys/values.
+		uint32_t off = (idx == 0) ? 0 : offsets[idx - 1];
+		uint2 rect_min, rect_max;
+
+		getRect(points_xy[idx], radii[idx], rect_min, rect_max, grid);
+
+		// For each tile that the bounding rect overlaps, emit a 
+		// key/value pair. The key is |  tile ID  |      depth      |,
+		// and the value is the ID of the Gaussian. Sorting the values 
+		// with this key yields Gaussian IDs in a list, such that they
+		// are first sorted by tile and then by depth. 
+		for (int y = rect_min.y; y < rect_max.y; y++)
+		{
+			for (int x = rect_min.x; x < rect_max.x; x++)
+			{
+				uint64_t key = y * grid.x + x;
+				key <<= 32;
+				key |= *((uint32_t*)&depths[idx]);
+				gaussian_keys_unsorted[off] = key;
+				gaussian_values_unsorted[off] = idx;
+				off++;
+			}
+		}
+	}
+}
+
+// Check keys to see if it is at the start/end of one tile's range in 
+// the full sorted list. If yes, write start/end of this tile. 
+// Run once per instanced (duplicated) Gaussian ID.
+__global__ void identifyTileRanges(int L, uint64_t* point_list_keys, uint2* ranges)
+{
+	auto idx = cg::this_grid().thread_rank();
+	if (idx >= L)
+		return;
+
+	// Read tile ID from key. Update start/end of tile range if at limit.
+	uint64_t key = point_list_keys[idx];
+	uint32_t currtile = key >> 32;
+	if (idx == 0)
+		ranges[currtile].x = 0;
+	else
+	{
+		uint32_t prevtile = point_list_keys[idx - 1] >> 32;
+		if (currtile != prevtile)
+		{
+			ranges[prevtile].y = idx;
+			ranges[currtile].x = idx;
+		}
+	}
+	if (idx == L - 1)
+		ranges[currtile].y = L;
+}
+
+// Mark Gaussians as visible/invisible, based on view frustum testing
+void CudaRasterizer::Rasterizer::markVisible(
+	int P,
+	float* means3D,
+	float* viewmatrix,
+	float* projmatrix,
+	bool* present)
+{
+	checkFrustum << <(P + 255) / 256, 256 >> > (
+		P,
+		means3D,
+		viewmatrix, projmatrix,
+		present);
+}
+
+CudaRasterizer::GeometryState CudaRasterizer::GeometryState::fromChunk(char*& chunk, size_t P)
+{
+	GeometryState geom;
+	obtain(chunk, geom.depths, P, 128);
+	obtain(chunk, geom.clamped, P * 3, 128);
+	obtain(chunk, geom.internal_radii, P, 128);
+	obtain(chunk, geom.means2D, P, 128);
+	obtain(chunk, geom.cov3D, P * 6, 128);
+	obtain(chunk, geom.conic_opacity, P, 128);
+	obtain(chunk, geom.rgb, P * 3, 128);
+	obtain(chunk, geom.tiles_touched, P, 128);
+	cub::DeviceScan::InclusiveSum(nullptr, geom.scan_size, geom.tiles_touched, geom.tiles_touched, P);
+	obtain(chunk, geom.scanning_space, geom.scan_size, 128);
+	obtain(chunk, geom.point_offsets, P, 128);
+	return geom;
+}
+
+CudaRasterizer::ImageState CudaRasterizer::ImageState::fromChunk(char*& chunk, size_t N)
+{
+	ImageState img;
+	obtain(chunk, img.accum_alpha, N, 128);
+	obtain(chunk, img.n_contrib, N, 128);
+	obtain(chunk, img.ranges, N, 128);
+	return img;
+}
+
+CudaRasterizer::BinningState CudaRasterizer::BinningState::fromChunk(char*& chunk, size_t P)
+{
+	BinningState binning;
+	obtain(chunk, binning.point_list, P, 128);
+	obtain(chunk, binning.point_list_unsorted, P, 128);
+	obtain(chunk, binning.point_list_keys, P, 128);
+	obtain(chunk, binning.point_list_keys_unsorted, P, 128);
+	cub::DeviceRadixSort::SortPairs(
+		nullptr, binning.sorting_size,
+		binning.point_list_keys_unsorted, binning.point_list_keys,
+		binning.point_list_unsorted, binning.point_list, P);
+	obtain(chunk, binning.list_sorting_space, binning.sorting_size, 128);
+	return binning;
+}
+
+// Forward rendering procedure for differentiable rasterization
+// of Gaussians.
+int CudaRasterizer::Rasterizer::forward(
+	std::function<char* (size_t)> geometryBuffer,
+	std::function<char* (size_t)> binningBuffer,
+	std::function<char* (size_t)> imageBuffer,
+	const int P, int D, int M,
+	const float* background,
+	const int width, int height,
+	const float* means3D,
+	const float* shs,
+	const float* colors_precomp,
+	const float* opacities,
+	const float* scales,
+	const float scale_modifier,
+	const float* rotations,
+	const float* cov3D_precomp,
+	const float* viewmatrix,
+	const float* projmatrix,
+	const float* cam_pos,
+	const float tan_fovx, float tan_fovy,
+	const bool prefiltered,
+	float* out_color,
+	float* out_depth,
+	int* radii,
+	bool debug)
+{
+	const float focal_y = height / (2.0f * tan_fovy);
+	const float focal_x = width / (2.0f * tan_fovx);
+
+	size_t chunk_size = required<GeometryState>(P);
+	char* chunkptr = geometryBuffer(chunk_size);
+	GeometryState geomState = GeometryState::fromChunk(chunkptr, P);
+
+	if (radii == nullptr)
+	{
+		radii = geomState.internal_radii;
+	}
+
+	dim3 tile_grid((width + BLOCK_X - 1) / BLOCK_X, (height + BLOCK_Y - 1) / BLOCK_Y, 1);
+	dim3 block(BLOCK_X, BLOCK_Y, 1);
+
+	// Dynamically resize image-based auxiliary buffers during training
+	size_t img_chunk_size = required<ImageState>(width * height);
+	char* img_chunkptr = imageBuffer(img_chunk_size);
+	ImageState imgState = ImageState::fromChunk(img_chunkptr, width * height);
+
+	if (NUM_CHANNELS != 3 && colors_precomp == nullptr)
+	{
+		throw std::runtime_error("For non-RGB, provide precomputed Gaussian colors!");
+	}
+
+	// Run preprocessing per-Gaussian (transformation, bounding, conversion of SHs to RGB)
+	CHECK_CUDA(FORWARD::preprocess(
+		P, D, M,
+		means3D,
+		(glm::vec3*)scales,
+		scale_modifier,
+		(glm::vec4*)rotations,
+		opacities,
+		shs,
+		geomState.clamped,
+		cov3D_precomp,
+		colors_precomp,
+		viewmatrix, projmatrix,
+		(glm::vec3*)cam_pos,
+		width, height,
+		focal_x, focal_y,
+		tan_fovx, tan_fovy,
+		radii,
+		geomState.means2D,
+		geomState.depths,
+		geomState.cov3D,
+		geomState.rgb,
+		geomState.conic_opacity,
+		tile_grid,
+		geomState.tiles_touched,
+		prefiltered
+	), debug)
+
+	// Compute prefix sum over full list of touched tile counts by Gaussians
+	// E.g., [2, 3, 0, 2, 1] -> [2, 5, 5, 7, 8]
+	CHECK_CUDA(cub::DeviceScan::InclusiveSum(geomState.scanning_space, geomState.scan_size, geomState.tiles_touched, geomState.point_offsets, P), debug)
+
+	// Retrieve total number of Gaussian instances to launch and resize aux buffers
+	int num_rendered;
+	CHECK_CUDA(cudaMemcpy(&num_rendered, geomState.point_offsets + P - 1, sizeof(int), cudaMemcpyDeviceToHost), debug);
+
+	size_t binning_chunk_size = required<BinningState>(num_rendered);
+	char* binning_chunkptr = binningBuffer(binning_chunk_size);
+	BinningState binningState = BinningState::fromChunk(binning_chunkptr, num_rendered);
+
+	// For each instance to be rendered, produce adequate [ tile | depth ] key 
+	// and corresponding dublicated Gaussian indices to be sorted
+	duplicateWithKeys << <(P + 255) / 256, 256 >> > (
+		P,
+		geomState.means2D,
+		geomState.depths,
+		geomState.point_offsets,
+		binningState.point_list_keys_unsorted,
+		binningState.point_list_unsorted,
+		radii,
+		tile_grid)
+	CHECK_CUDA(, debug)
+
+	int bit = getHigherMsb(tile_grid.x * tile_grid.y);
+
+	// Sort complete list of (duplicated) Gaussian indices by keys
+	CHECK_CUDA(cub::DeviceRadixSort::SortPairs(
+		binningState.list_sorting_space,
+		binningState.sorting_size,
+		binningState.point_list_keys_unsorted, binningState.point_list_keys,
+		binningState.point_list_unsorted, binningState.point_list,
+		num_rendered, 0, 32 + bit), debug)
+
+	CHECK_CUDA(cudaMemset(imgState.ranges, 0, tile_grid.x * tile_grid.y * sizeof(uint2)), debug);
+
+	// Identify start and end of per-tile workloads in sorted list
+	if (num_rendered > 0)
+		identifyTileRanges << <(num_rendered + 255) / 256, 256 >> > (
+			num_rendered,
+			binningState.point_list_keys,
+			imgState.ranges);
+	CHECK_CUDA(, debug)
+
+	// Let each tile blend its range of Gaussians independently in parallel
+	const float* feature_ptr = colors_precomp != nullptr ? colors_precomp : geomState.rgb;
+	CHECK_CUDA(FORWARD::render(
+		tile_grid, block,
+		imgState.ranges,
+		binningState.point_list,
+		width, height,
+		geomState.means2D,
+		feature_ptr,
+		geomState.depths,
+		geomState.conic_opacity,
+		imgState.accum_alpha,
+		imgState.n_contrib,
+		background,
+		out_color,
+		out_depth), debug)
+
+	return num_rendered;
+}
+
+// Produce necessary gradients for optimization, corresponding
+// to forward render pass
+void CudaRasterizer::Rasterizer::backward(
+	const int P, int D, int M, int R,
+	const float* background,
+	const int width, int height,
+	const float* means3D,
+	const float* shs,
+	const float* colors_precomp,
+	const float* scales,
+	const float scale_modifier,
+	const float* rotations,
+	const float* cov3D_precomp,
+	const float* viewmatrix,
+	const float* projmatrix,
+	const float* campos,
+	const float tan_fovx, float tan_fovy,
+	const int* radii,
+	char* geom_buffer,
+	char* binning_buffer,
+	char* img_buffer,
+	const float* dL_dpix,
+	const float* dL_depths,
+	float* dL_dmean2D,
+	float* dL_dconic,
+	float* dL_dopacity,
+	float* dL_dcolor,
+	float* dL_dmean3D,
+	float* dL_dcov3D,
+	float* dL_dsh,
+	float* dL_dscale,
+	float* dL_drot,
+	bool debug)
+{
+	GeometryState geomState = GeometryState::fromChunk(geom_buffer, P);
+	BinningState binningState = BinningState::fromChunk(binning_buffer, R);
+	ImageState imgState = ImageState::fromChunk(img_buffer, width * height);
+
+	if (radii == nullptr)
+	{
+		radii = geomState.internal_radii;
+	}
+
+	const float focal_y = height / (2.0f * tan_fovy);
+	const float focal_x = width / (2.0f * tan_fovx);
+
+	const dim3 tile_grid((width + BLOCK_X - 1) / BLOCK_X, (height + BLOCK_Y - 1) / BLOCK_Y, 1);
+	const dim3 block(BLOCK_X, BLOCK_Y, 1);
+
+	// Compute loss gradients w.r.t. 2D mean position, conic matrix,
+	// opacity and RGB of Gaussians from per-pixel loss gradients.
+	// If we were given precomputed colors and not SHs, use them.
+	const float* color_ptr = (colors_precomp != nullptr) ? colors_precomp : geomState.rgb;
+	const float* depth_ptr = geomState.depths;
+	CHECK_CUDA(BACKWARD::render(
+		tile_grid,
+		block,
+		imgState.ranges,
+		binningState.point_list,
+		width, height,
+		background,
+		geomState.means2D,
+		geomState.conic_opacity,
+		(float3*)means3D,
+		color_ptr,
+		depth_ptr,
+		projmatrix,
+		imgState.accum_alpha,
+		imgState.n_contrib,
+		dL_dpix,
+		dL_depths,
+		(float3*)dL_dmean2D,
+		(float4*)dL_dconic,
+		(float3*)dL_dmean3D,
+		dL_dopacity,
+		dL_dcolor), debug)
+
+	// Take care of the rest of preprocessing. Was the precomputed covariance
+	// given to us or a scales/rot pair? If precomputed, pass that. If not,
+	// use the one we computed ourselves.
+	const float* cov3D_ptr = (cov3D_precomp != nullptr) ? cov3D_precomp : geomState.cov3D;
+	CHECK_CUDA(BACKWARD::preprocess(P, D, M,
+		(float3*)means3D,
+		radii,
+		shs,
+		geomState.clamped,
+		(glm::vec3*)scales,
+		(glm::vec4*)rotations,
+		scale_modifier,
+		cov3D_ptr,
+		viewmatrix,
+		projmatrix,
+		focal_x, focal_y,
+		tan_fovx, tan_fovy,
+		(glm::vec3*)campos,
+		(float3*)dL_dmean2D,
+		dL_dconic,
+		(glm::vec3*)dL_dmean3D,
+		dL_dcolor,
+		dL_dcov3D,
+		dL_dsh,
+		(glm::vec3*)dL_dscale,
+		(glm::vec4*)dL_drot), debug)
+}

submodules/depth-diff-gaussian-rasterization-min/cuda_rasterizer/rasterizer_impl.h

@@ -0,0 +1,74 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#pragma once
+
+#include <iostream>
+#include <vector>
+#include "rasterizer.h"
+#include <cuda_runtime_api.h>
+
+namespace CudaRasterizer
+{
+	template <typename T>
+	static void obtain(char*& chunk, T*& ptr, std::size_t count, std::size_t alignment)
+	{
+		std::size_t offset = (reinterpret_cast<std::uintptr_t>(chunk) + alignment - 1) & ~(alignment - 1);
+		ptr = reinterpret_cast<T*>(offset);
+		chunk = reinterpret_cast<char*>(ptr + count);
+	}
+
+	struct GeometryState
+	{
+		size_t scan_size;
+		float* depths;
+		char* scanning_space;
+		bool* clamped;
+		int* internal_radii;
+		float2* means2D;
+		float* cov3D;
+		float4* conic_opacity;
+		float* rgb;
+		uint32_t* point_offsets;
+		uint32_t* tiles_touched;
+
+		static GeometryState fromChunk(char*& chunk, size_t P);
+	};
+
+	struct ImageState
+	{
+		uint2* ranges;
+		uint32_t* n_contrib;
+		float* accum_alpha;
+
+		static ImageState fromChunk(char*& chunk, size_t N);
+	};
+
+	struct BinningState
+	{
+		size_t sorting_size;
+		uint64_t* point_list_keys_unsorted;
+		uint64_t* point_list_keys;
+		uint32_t* point_list_unsorted;
+		uint32_t* point_list;
+		char* list_sorting_space;
+
+		static BinningState fromChunk(char*& chunk, size_t P);
+	};
+
+	template<typename T> 
+	size_t required(size_t P)
+	{
+		char* size = nullptr;
+		T::fromChunk(size, P);
+		return ((size_t)size) + 128;
+	}
+};

submodules/depth-diff-gaussian-rasterization-min/depth_diff_gaussian_rasterization_min.egg-info/PKG-INFO

@@ -0,0 +1,4 @@
+Metadata-Version: 2.1
+Name: depth-diff-gaussian-rasterization-min
+Version: 0.0.0
+License-File: LICENSE.md

submodules/depth-diff-gaussian-rasterization-min/depth_diff_gaussian_rasterization_min.egg-info/SOURCES.txt

@@ -0,0 +1,13 @@
+LICENSE.md
+README.md
+ext.cpp
+rasterize_points.cu
+setup.py
+cuda_rasterizer/backward.cu
+cuda_rasterizer/forward.cu
+cuda_rasterizer/rasterizer_impl.cu
+depth_diff_gaussian_rasterization_min/__init__.py
+depth_diff_gaussian_rasterization_min.egg-info/PKG-INFO
+depth_diff_gaussian_rasterization_min.egg-info/SOURCES.txt
+depth_diff_gaussian_rasterization_min.egg-info/dependency_links.txt
+depth_diff_gaussian_rasterization_min.egg-info/top_level.txt

submodules/depth-diff-gaussian-rasterization-min/depth_diff_gaussian_rasterization_min.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

submodules/depth-diff-gaussian-rasterization-min/depth_diff_gaussian_rasterization_min.egg-info/top_level.txt

@@ -0,0 +1 @@
+depth_diff_gaussian_rasterization_min

submodules/depth-diff-gaussian-rasterization-min/depth_diff_gaussian_rasterization_min/.ipynb_checkpoints/__init__-checkpoint.py

@@ -0,0 +1,222 @@
+#
+# Copyright (C) 2023, Inria
+# GRAPHDECO research group, https://team.inria.fr/graphdeco
+# All rights reserved.
+#
+# This software is free for non-commercial, research and evaluation use 
+# under the terms of the LICENSE.md file.
+#
+# For inquiries contact  george.drettakis@inria.fr
+#
+
+from typing import NamedTuple
+import torch.nn as nn
+import torch
+from . import _C
+
+def cpu_deep_copy_tuple(input_tuple):
+    copied_tensors = [item.cpu().clone() if isinstance(item, torch.Tensor) else item for item in input_tuple]
+    return tuple(copied_tensors)
+
+def rasterize_gaussians(
+    means3D,
+    means2D,
+    sh,
+    colors_precomp,
+    opacities,
+    scales,
+    rotations,
+    cov3Ds_precomp,
+    raster_settings,
+):
+    return _RasterizeGaussians.apply(
+        means3D,
+        means2D,
+        sh,
+        colors_precomp,
+        opacities,
+        scales,
+        rotations,
+        cov3Ds_precomp,
+        raster_settings,
+    )
+
+class _RasterizeGaussians(torch.autograd.Function):
+    @staticmethod
+    def forward(
+        ctx,
+        means3D,
+        means2D,
+        sh,
+        colors_precomp,
+        opacities,
+        scales,
+        rotations,
+        cov3Ds_precomp,
+        raster_settings,
+    ):
+
+        # Restructure arguments the way that the C++ lib expects them
+        args = (
+            raster_settings.bg, 
+            means3D,
+            colors_precomp,
+            opacities,
+            scales,
+            rotations,
+            raster_settings.scale_modifier,
+            cov3Ds_precomp,
+            raster_settings.viewmatrix,
+            raster_settings.projmatrix,
+            raster_settings.tanfovx,
+            raster_settings.tanfovy,
+            raster_settings.image_height,
+            raster_settings.image_width,
+            sh,
+            raster_settings.sh_degree,
+            raster_settings.campos,
+            raster_settings.prefiltered,
+            raster_settings.debug
+        )
+
+        # Invoke C++/CUDA rasterizer
+        if raster_settings.debug:
+            cpu_args = cpu_deep_copy_tuple(args) # Copy them before they can be corrupted
+            try:
+                num_rendered, color, depth, radii, geomBuffer, binningBuffer, imgBuffer = _C.rasterize_gaussians(*args)
+            except Exception as ex:
+                torch.save(cpu_args, "snapshot_fw.dump")
+                print("\nAn error occured in forward. Please forward snapshot_fw.dump for debugging.")
+                raise ex
+        else:
+            num_rendered, color, depth, radii, geomBuffer, binningBuffer, imgBuffer = _C.rasterize_gaussians(*args)
+
+        # Keep relevant tensors for backward
+        ctx.raster_settings = raster_settings
+        ctx.num_rendered = num_rendered
+        ctx.save_for_backward(colors_precomp, means3D, scales, rotations, cov3Ds_precomp, radii, sh, geomBuffer, binningBuffer, imgBuffer)
+        return color, radii, depth
+
+    @staticmethod
+    def backward(ctx, grad_out_color, grad_radii, grad_depth):
+
+        # Restore necessary values from context
+        num_rendered = ctx.num_rendered
+        raster_settings = ctx.raster_settings
+        colors_precomp, means3D, scales, rotations, cov3Ds_precomp, radii, sh, geomBuffer, binningBuffer, imgBuffer = ctx.saved_tensors
+
+        # Restructure args as C++ method expects them
+        args = (raster_settings.bg,
+                means3D, 
+                radii, 
+                colors_precomp, 
+                scales, 
+                rotations, 
+                raster_settings.scale_modifier, 
+                cov3Ds_precomp, 
+                raster_settings.viewmatrix, 
+                raster_settings.projmatrix, 
+                raster_settings.tanfovx, 
+                raster_settings.tanfovy, 
+                grad_out_color,
+                grad_depth,
+                sh, 
+                raster_settings.sh_degree, 
+                raster_settings.campos,
+                geomBuffer,
+                num_rendered,
+                binningBuffer,
+                imgBuffer,
+                raster_settings.debug)
+
+        # Compute gradients for relevant tensors by invoking backward method
+        if raster_settings.debug:
+            cpu_args = cpu_deep_copy_tuple(args) # Copy them before they can be corrupted
+            try:
+                grad_means2D, grad_colors_precomp, grad_opacities, grad_means3D, grad_cov3Ds_precomp, grad_sh, grad_scales, grad_rotations = _C.rasterize_gaussians_backward(*args)
+            except Exception as ex:
+                torch.save(cpu_args, "snapshot_bw.dump")
+                print("\nAn error occured in backward. Writing snapshot_bw.dump for debugging.\n")
+                raise ex
+        else:
+             grad_means2D, grad_colors_precomp, grad_opacities, grad_means3D, grad_cov3Ds_precomp, grad_sh, grad_scales, grad_rotations = _C.rasterize_gaussians_backward(*args)
+
+        grads = (
+            grad_means3D,
+            grad_means2D,
+            grad_sh,
+            grad_colors_precomp,
+            grad_opacities,
+            grad_scales,
+            grad_rotations,
+            grad_cov3Ds_precomp,
+            None,
+        )
+
+        return grads
+
+class GaussianRasterizationSettings(NamedTuple):
+    image_height: int
+    image_width: int 
+    tanfovx : float
+    tanfovy : float
+    bg : torch.Tensor
+    scale_modifier : float
+    viewmatrix : torch.Tensor
+    projmatrix : torch.Tensor
+    sh_degree : int
+    campos : torch.Tensor
+    prefiltered : bool
+    debug : bool
+
+class GaussianRasterizer(nn.Module):
+    def __init__(self, raster_settings):
+        super().__init__()
+        self.raster_settings = raster_settings
+
+    def markVisible(self, positions):
+        # Mark visible points (based on frustum culling for camera) with a boolean 
+        with torch.no_grad():
+            raster_settings = self.raster_settings
+            visible = _C.mark_visible(
+                positions,
+                raster_settings.viewmatrix,
+                raster_settings.projmatrix)
+            
+        return visible
+
+    def forward(self, means3D, means2D, opacities, shs = None, colors_precomp = None, scales = None, rotations = None, cov3D_precomp = None):
+        
+        raster_settings = self.raster_settings
+
+        if (shs is None and colors_precomp is None) or (shs is not None and colors_precomp is not None):
+            raise Exception('Please provide excatly one of either SHs or precomputed colors!')
+        
+        if ((scales is None or rotations is None) and cov3D_precomp is None) or ((scales is not None or rotations is not None) and cov3D_precomp is not None):
+            raise Exception('Please provide exactly one of either scale/rotation pair or precomputed 3D covariance!')
+        
+        if shs is None:
+            shs = torch.Tensor([])
+        if colors_precomp is None:
+            colors_precomp = torch.Tensor([])
+
+        if scales is None:
+            scales = torch.Tensor([])
+        if rotations is None:
+            rotations = torch.Tensor([])
+        if cov3D_precomp is None:
+            cov3D_precomp = torch.Tensor([])
+
+        # Invoke C++/CUDA rasterization routine
+        return rasterize_gaussians(
+            means3D,
+            means2D,
+            shs,
+            colors_precomp,
+            opacities,
+            scales, 
+            rotations,
+            cov3D_precomp,
+            raster_settings, 
+        )
+

submodules/depth-diff-gaussian-rasterization-min/depth_diff_gaussian_rasterization_min/__init__.py

@@ -0,0 +1,222 @@
+#
+# Copyright (C) 2023, Inria
+# GRAPHDECO research group, https://team.inria.fr/graphdeco
+# All rights reserved.
+#
+# This software is free for non-commercial, research and evaluation use 
+# under the terms of the LICENSE.md file.
+#
+# For inquiries contact  george.drettakis@inria.fr
+#
+
+from typing import NamedTuple
+import torch.nn as nn
+import torch
+from . import _C
+
+def cpu_deep_copy_tuple(input_tuple):
+    copied_tensors = [item.cpu().clone() if isinstance(item, torch.Tensor) else item for item in input_tuple]
+    return tuple(copied_tensors)
+
+def rasterize_gaussians(
+    means3D,
+    means2D,
+    sh,
+    colors_precomp,
+    opacities,
+    scales,
+    rotations,
+    cov3Ds_precomp,
+    raster_settings,
+):
+    return _RasterizeGaussians.apply(
+        means3D,
+        means2D,
+        sh,
+        colors_precomp,
+        opacities,
+        scales,
+        rotations,
+        cov3Ds_precomp,
+        raster_settings,
+    )
+
+class _RasterizeGaussians(torch.autograd.Function):
+    @staticmethod
+    def forward(
+        ctx,
+        means3D,
+        means2D,
+        sh,
+        colors_precomp,
+        opacities,
+        scales,
+        rotations,
+        cov3Ds_precomp,
+        raster_settings,
+    ):
+
+        # Restructure arguments the way that the C++ lib expects them
+        args = (
+            raster_settings.bg, 
+            means3D,
+            colors_precomp,
+            opacities,
+            scales,
+            rotations,
+            raster_settings.scale_modifier,
+            cov3Ds_precomp,
+            raster_settings.viewmatrix,
+            raster_settings.projmatrix,
+            raster_settings.tanfovx,
+            raster_settings.tanfovy,
+            raster_settings.image_height,
+            raster_settings.image_width,
+            sh,
+            raster_settings.sh_degree,
+            raster_settings.campos,
+            raster_settings.prefiltered,
+            raster_settings.debug
+        )
+
+        # Invoke C++/CUDA rasterizer
+        if raster_settings.debug:
+            cpu_args = cpu_deep_copy_tuple(args) # Copy them before they can be corrupted
+            try:
+                num_rendered, color, depth, radii, geomBuffer, binningBuffer, imgBuffer = _C.rasterize_gaussians(*args)
+            except Exception as ex:
+                torch.save(cpu_args, "snapshot_fw.dump")
+                print("\nAn error occured in forward. Please forward snapshot_fw.dump for debugging.")
+                raise ex
+        else:
+            num_rendered, color, depth, radii, geomBuffer, binningBuffer, imgBuffer = _C.rasterize_gaussians(*args)
+
+        # Keep relevant tensors for backward
+        ctx.raster_settings = raster_settings
+        ctx.num_rendered = num_rendered
+        ctx.save_for_backward(colors_precomp, means3D, scales, rotations, cov3Ds_precomp, radii, sh, geomBuffer, binningBuffer, imgBuffer)
+        return color, radii, depth
+
+    @staticmethod
+    def backward(ctx, grad_out_color, grad_radii, grad_depth):
+
+        # Restore necessary values from context
+        num_rendered = ctx.num_rendered
+        raster_settings = ctx.raster_settings
+        colors_precomp, means3D, scales, rotations, cov3Ds_precomp, radii, sh, geomBuffer, binningBuffer, imgBuffer = ctx.saved_tensors
+
+        # Restructure args as C++ method expects them
+        args = (raster_settings.bg,
+                means3D, 
+                radii, 
+                colors_precomp, 
+                scales, 
+                rotations, 
+                raster_settings.scale_modifier, 
+                cov3Ds_precomp, 
+                raster_settings.viewmatrix, 
+                raster_settings.projmatrix, 
+                raster_settings.tanfovx, 
+                raster_settings.tanfovy, 
+                grad_out_color,
+                grad_depth,
+                sh, 
+                raster_settings.sh_degree, 
+                raster_settings.campos,
+                geomBuffer,
+                num_rendered,
+                binningBuffer,
+                imgBuffer,
+                raster_settings.debug)
+
+        # Compute gradients for relevant tensors by invoking backward method
+        if raster_settings.debug:
+            cpu_args = cpu_deep_copy_tuple(args) # Copy them before they can be corrupted
+            try:
+                grad_means2D, grad_colors_precomp, grad_opacities, grad_means3D, grad_cov3Ds_precomp, grad_sh, grad_scales, grad_rotations = _C.rasterize_gaussians_backward(*args)
+            except Exception as ex:
+                torch.save(cpu_args, "snapshot_bw.dump")
+                print("\nAn error occured in backward. Writing snapshot_bw.dump for debugging.\n")
+                raise ex
+        else:
+             grad_means2D, grad_colors_precomp, grad_opacities, grad_means3D, grad_cov3Ds_precomp, grad_sh, grad_scales, grad_rotations = _C.rasterize_gaussians_backward(*args)
+
+        grads = (
+            grad_means3D,
+            grad_means2D,
+            grad_sh,
+            grad_colors_precomp,
+            grad_opacities,
+            grad_scales,
+            grad_rotations,
+            grad_cov3Ds_precomp,
+            None,
+        )
+
+        return grads
+
+class GaussianRasterizationSettings(NamedTuple):
+    image_height: int
+    image_width: int 
+    tanfovx : float
+    tanfovy : float
+    bg : torch.Tensor
+    scale_modifier : float
+    viewmatrix : torch.Tensor
+    projmatrix : torch.Tensor
+    sh_degree : int
+    campos : torch.Tensor
+    prefiltered : bool
+    debug : bool
+
+class GaussianRasterizer(nn.Module):
+    def __init__(self, raster_settings):
+        super().__init__()
+        self.raster_settings = raster_settings
+
+    def markVisible(self, positions):
+        # Mark visible points (based on frustum culling for camera) with a boolean 
+        with torch.no_grad():
+            raster_settings = self.raster_settings
+            visible = _C.mark_visible(
+                positions,
+                raster_settings.viewmatrix,
+                raster_settings.projmatrix)
+            
+        return visible
+
+    def forward(self, means3D, means2D, opacities, shs = None, colors_precomp = None, scales = None, rotations = None, cov3D_precomp = None):
+        
+        raster_settings = self.raster_settings
+
+        if (shs is None and colors_precomp is None) or (shs is not None and colors_precomp is not None):
+            raise Exception('Please provide excatly one of either SHs or precomputed colors!')
+        
+        if ((scales is None or rotations is None) and cov3D_precomp is None) or ((scales is not None or rotations is not None) and cov3D_precomp is not None):
+            raise Exception('Please provide exactly one of either scale/rotation pair or precomputed 3D covariance!')
+        
+        if shs is None:
+            shs = torch.Tensor([])
+        if colors_precomp is None:
+            colors_precomp = torch.Tensor([])
+
+        if scales is None:
+            scales = torch.Tensor([])
+        if rotations is None:
+            rotations = torch.Tensor([])
+        if cov3D_precomp is None:
+            cov3D_precomp = torch.Tensor([])
+
+        # Invoke C++/CUDA rasterization routine
+        return rasterize_gaussians(
+            means3D,
+            means2D,
+            shs,
+            colors_precomp,
+            opacities,
+            scales, 
+            rotations,
+            cov3D_precomp,
+            raster_settings, 
+        )
+

submodules/depth-diff-gaussian-rasterization-min/ext.cpp

@@ -0,0 +1,19 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#include <torch/extension.h>
+#include "rasterize_points.h"
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+  m.def("rasterize_gaussians", &RasterizeGaussiansCUDA);
+  m.def("rasterize_gaussians_backward", &RasterizeGaussiansBackwardCUDA);
+  m.def("mark_visible", &markVisible);
+}

submodules/depth-diff-gaussian-rasterization-min/rasterize_points.cu

@@ -0,0 +1,221 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#include <math.h>
+#include <torch/extension.h>
+#include <cstdio>
+#include <sstream>
+#include <iostream>
+#include <tuple>
+#include <stdio.h>
+#include <cuda_runtime_api.h>
+#include <memory>
+#include "cuda_rasterizer/config.h"
+#include "cuda_rasterizer/rasterizer.h"
+#include <fstream>
+#include <string>
+#include <functional>
+
+std::function<char*(size_t N)> resizeFunctional(torch::Tensor& t) {
+    auto lambda = [&t](size_t N) {
+        t.resize_({(long long)N});
+		return reinterpret_cast<char*>(t.contiguous().data_ptr());
+    };
+    return lambda;
+}
+
+std::tuple<int, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor>
+RasterizeGaussiansCUDA(
+	const torch::Tensor& background,
+	const torch::Tensor& means3D,
+    const torch::Tensor& colors,
+    const torch::Tensor& opacity,
+	const torch::Tensor& scales,
+	const torch::Tensor& rotations,
+	const float scale_modifier,
+	const torch::Tensor& cov3D_precomp,
+	const torch::Tensor& viewmatrix,
+	const torch::Tensor& projmatrix,
+	const float tan_fovx, 
+	const float tan_fovy,
+    const int image_height,
+    const int image_width,
+	const torch::Tensor& sh,
+	const int degree,
+	const torch::Tensor& campos,
+	const bool prefiltered,
+	const bool debug)
+{
+  if (means3D.ndimension() != 2 || means3D.size(1) != 3) {
+    AT_ERROR("means3D must have dimensions (num_points, 3)");
+  }
+  
+  const int P = means3D.size(0);
+  const int H = image_height;
+  const int W = image_width;
+
+  auto int_opts = means3D.options().dtype(torch::kInt32);
+  auto float_opts = means3D.options().dtype(torch::kFloat32);
+
+  torch::Tensor out_color = torch::full({NUM_CHANNELS, H, W}, 0.0, float_opts);
+  torch::Tensor out_depth = torch::full({1, H, W}, 0.0, float_opts);
+  torch::Tensor radii = torch::full({P}, 0, means3D.options().dtype(torch::kInt32));
+  
+  torch::Device device(torch::kCUDA);
+  torch::TensorOptions options(torch::kByte);
+  torch::Tensor geomBuffer = torch::empty({0}, options.device(device));
+  torch::Tensor binningBuffer = torch::empty({0}, options.device(device));
+  torch::Tensor imgBuffer = torch::empty({0}, options.device(device));
+  std::function<char*(size_t)> geomFunc = resizeFunctional(geomBuffer);
+  std::function<char*(size_t)> binningFunc = resizeFunctional(binningBuffer);
+  std::function<char*(size_t)> imgFunc = resizeFunctional(imgBuffer);
+  
+  int rendered = 0;
+  if(P != 0)
+  {
+	  int M = 0;
+	  if(sh.size(0) != 0)
+	  {
+		M = sh.size(1);
+      }
+
+	  rendered = CudaRasterizer::Rasterizer::forward(
+	    geomFunc,
+		binningFunc,
+		imgFunc,
+	    P, degree, M,
+		background.contiguous().data<float>(),
+		W, H,
+		means3D.contiguous().data<float>(),
+		sh.contiguous().data_ptr<float>(),
+		colors.contiguous().data<float>(), 
+		opacity.contiguous().data<float>(), 
+		scales.contiguous().data_ptr<float>(),
+		scale_modifier,
+		rotations.contiguous().data_ptr<float>(),
+		cov3D_precomp.contiguous().data<float>(), 
+		viewmatrix.contiguous().data<float>(), 
+		projmatrix.contiguous().data<float>(),
+		campos.contiguous().data<float>(),
+		tan_fovx,
+		tan_fovy,
+		prefiltered,
+		out_color.contiguous().data<float>(),
+		out_depth.contiguous().data<float>(),
+		radii.contiguous().data<int>(),
+		debug);
+  }
+  return std::make_tuple(rendered, out_color, out_depth, radii, geomBuffer, binningBuffer, imgBuffer);
+}
+
+std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor>
+ RasterizeGaussiansBackwardCUDA(
+ 	const torch::Tensor& background,
+	const torch::Tensor& means3D,
+	const torch::Tensor& radii,
+    const torch::Tensor& colors,
+	const torch::Tensor& scales,
+	const torch::Tensor& rotations,
+	const float scale_modifier,
+	const torch::Tensor& cov3D_precomp,
+	const torch::Tensor& viewmatrix,
+    const torch::Tensor& projmatrix,
+	const float tan_fovx,
+	const float tan_fovy,
+    const torch::Tensor& dL_dout_color,
+        const torch::Tensor& dL_dout_depth,
+	const torch::Tensor& sh,
+	const int degree,
+	const torch::Tensor& campos,
+	const torch::Tensor& geomBuffer,
+	const int R,
+	const torch::Tensor& binningBuffer,
+	const torch::Tensor& imageBuffer,
+	const bool debug) 
+{
+  const int P = means3D.size(0);
+  const int H = dL_dout_color.size(1);
+  const int W = dL_dout_color.size(2);
+  
+  int M = 0;
+  if(sh.size(0) != 0)
+  {	
+	M = sh.size(1);
+  }
+
+  torch::Tensor dL_dmeans3D = torch::zeros({P, 3}, means3D.options());
+  torch::Tensor dL_dmeans2D = torch::zeros({P, 3}, means3D.options());
+  torch::Tensor dL_dcolors = torch::zeros({P, NUM_CHANNELS}, means3D.options());
+  torch::Tensor dL_dconic = torch::zeros({P, 2, 2}, means3D.options());
+  torch::Tensor dL_dopacity = torch::zeros({P, 1}, means3D.options());
+  torch::Tensor dL_dcov3D = torch::zeros({P, 6}, means3D.options());
+  torch::Tensor dL_dsh = torch::zeros({P, M, 3}, means3D.options());
+  torch::Tensor dL_dscales = torch::zeros({P, 3}, means3D.options());
+  torch::Tensor dL_drotations = torch::zeros({P, 4}, means3D.options());
+  
+  if(P != 0)
+  {  
+	  CudaRasterizer::Rasterizer::backward(P, degree, M, R,
+	  background.contiguous().data<float>(),
+	  W, H, 
+	  means3D.contiguous().data<float>(),
+	  sh.contiguous().data<float>(),
+	  colors.contiguous().data<float>(),
+	  scales.data_ptr<float>(),
+	  scale_modifier,
+	  rotations.data_ptr<float>(),
+	  cov3D_precomp.contiguous().data<float>(),
+	  viewmatrix.contiguous().data<float>(),
+	  projmatrix.contiguous().data<float>(),
+	  campos.contiguous().data<float>(),
+	  tan_fovx,
+	  tan_fovy,
+	  radii.contiguous().data<int>(),
+	  reinterpret_cast<char*>(geomBuffer.contiguous().data_ptr()),
+	  reinterpret_cast<char*>(binningBuffer.contiguous().data_ptr()),
+	  reinterpret_cast<char*>(imageBuffer.contiguous().data_ptr()),
+	  dL_dout_color.contiguous().data<float>(),
+	  dL_dout_depth.contiguous().data<float>(),
+	  dL_dmeans2D.contiguous().data<float>(),
+	  dL_dconic.contiguous().data<float>(),  
+	  dL_dopacity.contiguous().data<float>(),
+	  dL_dcolors.contiguous().data<float>(),
+	  dL_dmeans3D.contiguous().data<float>(),
+	  dL_dcov3D.contiguous().data<float>(),
+	  dL_dsh.contiguous().data<float>(),
+	  dL_dscales.contiguous().data<float>(),
+	  dL_drotations.contiguous().data<float>(),
+	  debug);
+  }
+
+  return std::make_tuple(dL_dmeans2D, dL_dcolors, dL_dopacity, dL_dmeans3D, dL_dcov3D, dL_dsh, dL_dscales, dL_drotations);
+}
+
+torch::Tensor markVisible(
+		torch::Tensor& means3D,
+		torch::Tensor& viewmatrix,
+		torch::Tensor& projmatrix)
+{ 
+  const int P = means3D.size(0);
+  
+  torch::Tensor present = torch::full({P}, false, means3D.options().dtype(at::kBool));
+ 
+  if(P != 0)
+  {
+	CudaRasterizer::Rasterizer::markVisible(P,
+		means3D.contiguous().data<float>(),
+		viewmatrix.contiguous().data<float>(),
+		projmatrix.contiguous().data<float>(),
+		present.contiguous().data<bool>());
+  }
+  
+  return present;
+}

submodules/depth-diff-gaussian-rasterization-min/rasterize_points.h

@@ -0,0 +1,68 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#pragma once
+#include <torch/extension.h>
+#include <cstdio>
+#include <tuple>
+#include <string>
+	
+std::tuple<int, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor>
+RasterizeGaussiansCUDA(
+	const torch::Tensor& background,
+	const torch::Tensor& means3D,
+    const torch::Tensor& colors,
+    const torch::Tensor& opacity,
+	const torch::Tensor& scales,
+	const torch::Tensor& rotations,
+	const float scale_modifier,
+	const torch::Tensor& cov3D_precomp,
+	const torch::Tensor& viewmatrix,
+	const torch::Tensor& projmatrix,
+	const float tan_fovx, 
+	const float tan_fovy,
+    const int image_height,
+    const int image_width,
+	const torch::Tensor& sh,
+	const int degree,
+	const torch::Tensor& campos,
+	const bool prefiltered,
+	const bool debug);
+
+std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor>
+ RasterizeGaussiansBackwardCUDA(
+ 	const torch::Tensor& background,
+	const torch::Tensor& means3D,
+	const torch::Tensor& radii,
+    const torch::Tensor& colors,
+	const torch::Tensor& scales,
+	const torch::Tensor& rotations,
+	const float scale_modifier,
+	const torch::Tensor& cov3D_precomp,
+	const torch::Tensor& viewmatrix,
+    const torch::Tensor& projmatrix,
+	const float tan_fovx, 
+	const float tan_fovy,
+    const torch::Tensor& dL_dout_color,
+        const torch::Tensor& dL_dout_depth,
+	const torch::Tensor& sh,
+	const int degree,
+	const torch::Tensor& campos,
+	const torch::Tensor& geomBuffer,
+	const int R,
+	const torch::Tensor& binningBuffer,
+	const torch::Tensor& imageBuffer,
+	const bool debug);
+		
+torch::Tensor markVisible(
+		torch::Tensor& means3D,
+		torch::Tensor& viewmatrix,
+		torch::Tensor& projmatrix);

submodules/depth-diff-gaussian-rasterization-min/setup.py

@@ -0,0 +1,34 @@
+#
+# Copyright (C) 2023, Inria
+# GRAPHDECO research group, https://team.inria.fr/graphdeco
+# All rights reserved.
+#
+# This software is free for non-commercial, research and evaluation use 
+# under the terms of the LICENSE.md file.
+#
+# For inquiries contact  george.drettakis@inria.fr
+#
+
+from setuptools import setup
+from torch.utils.cpp_extension import CUDAExtension, BuildExtension
+import os
+os.path.dirname(os.path.abspath(__file__))
+
+setup(
+    name="depth_diff_gaussian_rasterization_min",
+    packages=['depth_diff_gaussian_rasterization_min'],
+    ext_modules=[
+        CUDAExtension(
+            name="depth_diff_gaussian_rasterization_min._C",
+            sources=[
+            "cuda_rasterizer/rasterizer_impl.cu",
+            "cuda_rasterizer/forward.cu",
+            "cuda_rasterizer/backward.cu",
+            "rasterize_points.cu",
+            "ext.cpp"],
+            extra_compile_args={"nvcc": ["-I" + os.path.join(os.path.dirname(os.path.abspath(__file__)), "third_party/glm/")]})
+        ],
+    cmdclass={
+        'build_ext': BuildExtension
+    }
+)

submodules/depth-diff-gaussian-rasterization-min/third_party/stbi_image_write.h

@@ -0,0 +1,1724 @@
+/* stb_image_write - v1.16 - public domain - http://nothings.org/stb
+   writes out PNG/BMP/TGA/JPEG/HDR images to C stdio - Sean Barrett 2010-2015
+                                     no warranty implied; use at your own risk
+
+   Before #including,
+
+       #define STB_IMAGE_WRITE_IMPLEMENTATION
+
+   in the file that you want to have the implementation.
+
+   Will probably not work correctly with strict-aliasing optimizations.
+
+ABOUT:
+
+   This header file is a library for writing images to C stdio or a callback.
+
+   The PNG output is not optimal; it is 20-50% larger than the file
+   written by a decent optimizing implementation; though providing a custom
+   zlib compress function (see STBIW_ZLIB_COMPRESS) can mitigate that.
+   This library is designed for source code compactness and simplicity,
+   not optimal image file size or run-time performance.
+
+BUILDING:
+
+   You can #define STBIW_ASSERT(x) before the #include to avoid using assert.h.
+   You can #define STBIW_MALLOC(), STBIW_REALLOC(), and STBIW_FREE() to replace
+   malloc,realloc,free.
+   You can #define STBIW_MEMMOVE() to replace memmove()
+   You can #define STBIW_ZLIB_COMPRESS to use a custom zlib-style compress function
+   for PNG compression (instead of the builtin one), it must have the following signature:
+   unsigned char * my_compress(unsigned char *data, int data_len, int *out_len, int quality);
+   The returned data will be freed with STBIW_FREE() (free() by default),
+   so it must be heap allocated with STBIW_MALLOC() (malloc() by default),
+
+UNICODE:
+
+   If compiling for Windows and you wish to use Unicode filenames, compile
+   with
+       #define STBIW_WINDOWS_UTF8
+   and pass utf8-encoded filenames. Call stbiw_convert_wchar_to_utf8 to convert
+   Windows wchar_t filenames to utf8.
+
+USAGE:
+
+   There are five functions, one for each image file format:
+
+     int stbi_write_png(char const *filename, int w, int h, int comp, const void *data, int stride_in_bytes);
+     int stbi_write_bmp(char const *filename, int w, int h, int comp, const void *data);
+     int stbi_write_tga(char const *filename, int w, int h, int comp, const void *data);
+     int stbi_write_jpg(char const *filename, int w, int h, int comp, const void *data, int quality);
+     int stbi_write_hdr(char const *filename, int w, int h, int comp, const float *data);
+
+     void stbi_flip_vertically_on_write(int flag); // flag is non-zero to flip data vertically
+
+   There are also five equivalent functions that use an arbitrary write function. You are
+   expected to open/close your file-equivalent before and after calling these:
+
+     int stbi_write_png_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void  *data, int stride_in_bytes);
+     int stbi_write_bmp_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void  *data);
+     int stbi_write_tga_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void  *data);
+     int stbi_write_hdr_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const float *data);
+     int stbi_write_jpg_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data, int quality);
+
+   where the callback is:
+      void stbi_write_func(void *context, void *data, int size);
+
+   You can configure it with these global variables:
+      int stbi_write_tga_with_rle;             // defaults to true; set to 0 to disable RLE
+      int stbi_write_png_compression_level;    // defaults to 8; set to higher for more compression
+      int stbi_write_force_png_filter;         // defaults to -1; set to 0..5 to force a filter mode
+
+
+   You can define STBI_WRITE_NO_STDIO to disable the file variant of these
+   functions, so the library will not use stdio.h at all. However, this will
+   also disable HDR writing, because it requires stdio for formatted output.
+
+   Each function returns 0 on failure and non-0 on success.
+
+   The functions create an image file defined by the parameters. The image
+   is a rectangle of pixels stored from left-to-right, top-to-bottom.
+   Each pixel contains 'comp' channels of data stored interleaved with 8-bits
+   per channel, in the following order: 1=Y, 2=YA, 3=RGB, 4=RGBA. (Y is
+   monochrome color.) The rectangle is 'w' pixels wide and 'h' pixels tall.
+   The *data pointer points to the first byte of the top-left-most pixel.
+   For PNG, "stride_in_bytes" is the distance in bytes from the first byte of
+   a row of pixels to the first byte of the next row of pixels.
+
+   PNG creates output files with the same number of components as the input.
+   The BMP format expands Y to RGB in the file format and does not
+   output alpha.
+
+   PNG supports writing rectangles of data even when the bytes storing rows of
+   data are not consecutive in memory (e.g. sub-rectangles of a larger image),
+   by supplying the stride between the beginning of adjacent rows. The other
+   formats do not. (Thus you cannot write a native-format BMP through the BMP
+   writer, both because it is in BGR order and because it may have padding
+   at the end of the line.)
+
+   PNG allows you to set the deflate compression level by setting the global
+   variable 'stbi_write_png_compression_level' (it defaults to 8).
+
+   HDR expects linear float data. Since the format is always 32-bit rgb(e)
+   data, alpha (if provided) is discarded, and for monochrome data it is
+   replicated across all three channels.
+
+   TGA supports RLE or non-RLE compressed data. To use non-RLE-compressed
+   data, set the global variable 'stbi_write_tga_with_rle' to 0.
+
+   JPEG does ignore alpha channels in input data; quality is between 1 and 100.
+   Higher quality looks better but results in a bigger image.
+   JPEG baseline (no JPEG progressive).
+
+CREDITS:
+
+
+   Sean Barrett           -    PNG/BMP/TGA
+   Baldur Karlsson        -    HDR
+   Jean-Sebastien Guay    -    TGA monochrome
+   Tim Kelsey             -    misc enhancements
+   Alan Hickman           -    TGA RLE
+   Emmanuel Julien        -    initial file IO callback implementation
+   Jon Olick              -    original jo_jpeg.cpp code
+   Daniel Gibson          -    integrate JPEG, allow external zlib
+   Aarni Koskela          -    allow choosing PNG filter
+
+   bugfixes:
+      github:Chribba
+      Guillaume Chereau
+      github:jry2
+      github:romigrou
+      Sergio Gonzalez
+      Jonas Karlsson
+      Filip Wasil
+      Thatcher Ulrich
+      github:poppolopoppo
+      Patrick Boettcher
+      github:xeekworx
+      Cap Petschulat
+      Simon Rodriguez
+      Ivan Tikhonov
+      github:ignotion
+      Adam Schackart
+      Andrew Kensler
+
+LICENSE
+
+  See end of file for license information.
+
+*/
+
+#ifndef INCLUDE_STB_IMAGE_WRITE_H
+#define INCLUDE_STB_IMAGE_WRITE_H
+
+#include <stdlib.h>
+
+// if STB_IMAGE_WRITE_STATIC causes problems, try defining STBIWDEF to 'inline' or 'static inline'
+#ifndef STBIWDEF
+#ifdef STB_IMAGE_WRITE_STATIC
+#define STBIWDEF  static
+#else
+#ifdef __cplusplus
+#define STBIWDEF  extern "C"
+#else
+#define STBIWDEF  extern
+#endif
+#endif
+#endif
+
+#ifndef STB_IMAGE_WRITE_STATIC  // C++ forbids static forward declarations
+STBIWDEF int stbi_write_tga_with_rle;
+STBIWDEF int stbi_write_png_compression_level;
+STBIWDEF int stbi_write_force_png_filter;
+#endif
+
+#ifndef STBI_WRITE_NO_STDIO
+STBIWDEF int stbi_write_png(char const *filename, int w, int h, int comp, const void  *data, int stride_in_bytes);
+STBIWDEF int stbi_write_bmp(char const *filename, int w, int h, int comp, const void  *data);
+STBIWDEF int stbi_write_tga(char const *filename, int w, int h, int comp, const void  *data);
+STBIWDEF int stbi_write_hdr(char const *filename, int w, int h, int comp, const float *data);
+STBIWDEF int stbi_write_jpg(char const *filename, int x, int y, int comp, const void  *data, int quality);
+
+#ifdef STBIW_WINDOWS_UTF8
+STBIWDEF int stbiw_convert_wchar_to_utf8(char *buffer, size_t bufferlen, const wchar_t* input);
+#endif
+#endif
+
+typedef void stbi_write_func(void *context, void *data, int size);
+
+STBIWDEF int stbi_write_png_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void  *data, int stride_in_bytes);
+STBIWDEF int stbi_write_bmp_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void  *data);
+STBIWDEF int stbi_write_tga_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void  *data);
+STBIWDEF int stbi_write_hdr_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const float *data);
+STBIWDEF int stbi_write_jpg_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void  *data, int quality);
+
+STBIWDEF void stbi_flip_vertically_on_write(int flip_boolean);
+
+#endif//INCLUDE_STB_IMAGE_WRITE_H
+
+#ifdef STB_IMAGE_WRITE_IMPLEMENTATION
+
+#ifdef _WIN32
+   #ifndef _CRT_SECURE_NO_WARNINGS
+   #define _CRT_SECURE_NO_WARNINGS
+   #endif
+   #ifndef _CRT_NONSTDC_NO_DEPRECATE
+   #define _CRT_NONSTDC_NO_DEPRECATE
+   #endif
+#endif
+
+#ifndef STBI_WRITE_NO_STDIO
+#include <stdio.h>
+#endif // STBI_WRITE_NO_STDIO
+
+#include <stdarg.h>
+#include <stdlib.h>
+#include <string.h>
+#include <math.h>
+
+#if defined(STBIW_MALLOC) && defined(STBIW_FREE) && (defined(STBIW_REALLOC) || defined(STBIW_REALLOC_SIZED))
+// ok
+#elif !defined(STBIW_MALLOC) && !defined(STBIW_FREE) && !defined(STBIW_REALLOC) && !defined(STBIW_REALLOC_SIZED)
+// ok
+#else
+#error "Must define all or none of STBIW_MALLOC, STBIW_FREE, and STBIW_REALLOC (or STBIW_REALLOC_SIZED)."
+#endif
+
+#ifndef STBIW_MALLOC
+#define STBIW_MALLOC(sz)        malloc(sz)
+#define STBIW_REALLOC(p,newsz)  realloc(p,newsz)
+#define STBIW_FREE(p)           free(p)
+#endif
+
+#ifndef STBIW_REALLOC_SIZED
+#define STBIW_REALLOC_SIZED(p,oldsz,newsz) STBIW_REALLOC(p,newsz)
+#endif
+
+
+#ifndef STBIW_MEMMOVE
+#define STBIW_MEMMOVE(a,b,sz) memmove(a,b,sz)
+#endif
+
+
+#ifndef STBIW_ASSERT
+#include <assert.h>
+#define STBIW_ASSERT(x) assert(x)
+#endif
+
+#define STBIW_UCHAR(x) (unsigned char) ((x) & 0xff)
+
+#ifdef STB_IMAGE_WRITE_STATIC
+static int stbi_write_png_compression_level = 8;
+static int stbi_write_tga_with_rle = 1;
+static int stbi_write_force_png_filter = -1;
+#else
+int stbi_write_png_compression_level = 8;
+int stbi_write_tga_with_rle = 1;
+int stbi_write_force_png_filter = -1;
+#endif
+
+static int stbi__flip_vertically_on_write = 0;
+
+STBIWDEF void stbi_flip_vertically_on_write(int flag)
+{
+   stbi__flip_vertically_on_write = flag;
+}
+
+typedef struct
+{
+   stbi_write_func *func;
+   void *context;
+   unsigned char buffer[64];
+   int buf_used;
+} stbi__write_context;
+
+// initialize a callback-based context
+static void stbi__start_write_callbacks(stbi__write_context *s, stbi_write_func *c, void *context)
+{
+   s->func    = c;
+   s->context = context;
+}
+
+#ifndef STBI_WRITE_NO_STDIO
+
+static void stbi__stdio_write(void *context, void *data, int size)
+{
+   fwrite(data,1,size,(FILE*) context);
+}
+
+#if defined(_WIN32) && defined(STBIW_WINDOWS_UTF8)
+#ifdef __cplusplus
+#define STBIW_EXTERN extern "C"
+#else
+#define STBIW_EXTERN extern
+#endif
+STBIW_EXTERN __declspec(dllimport) int __stdcall MultiByteToWideChar(unsigned int cp, unsigned long flags, const char *str, int cbmb, wchar_t *widestr, int cchwide);
+STBIW_EXTERN __declspec(dllimport) int __stdcall WideCharToMultiByte(unsigned int cp, unsigned long flags, const wchar_t *widestr, int cchwide, char *str, int cbmb, const char *defchar, int *used_default);
+
+STBIWDEF int stbiw_convert_wchar_to_utf8(char *buffer, size_t bufferlen, const wchar_t* input)
+{
+   return WideCharToMultiByte(65001 /* UTF8 */, 0, input, -1, buffer, (int) bufferlen, NULL, NULL);
+}
+#endif
+
+static FILE *stbiw__fopen(char const *filename, char const *mode)
+{
+   FILE *f;
+#if defined(_WIN32) && defined(STBIW_WINDOWS_UTF8)
+   wchar_t wMode[64];
+   wchar_t wFilename[1024];
+   if (0 == MultiByteToWideChar(65001 /* UTF8 */, 0, filename, -1, wFilename, sizeof(wFilename)/sizeof(*wFilename)))
+      return 0;
+
+   if (0 == MultiByteToWideChar(65001 /* UTF8 */, 0, mode, -1, wMode, sizeof(wMode)/sizeof(*wMode)))
+      return 0;
+
+#if defined(_MSC_VER) && _MSC_VER >= 1400
+   if (0 != _wfopen_s(&f, wFilename, wMode))
+      f = 0;
+#else
+   f = _wfopen(wFilename, wMode);
+#endif
+
+#elif defined(_MSC_VER) && _MSC_VER >= 1400
+   if (0 != fopen_s(&f, filename, mode))
+      f=0;
+#else
+   f = fopen(filename, mode);
+#endif
+   return f;
+}
+
+static int stbi__start_write_file(stbi__write_context *s, const char *filename)
+{
+   FILE *f = stbiw__fopen(filename, "wb");
+   stbi__start_write_callbacks(s, stbi__stdio_write, (void *) f);
+   return f != NULL;
+}
+
+static void stbi__end_write_file(stbi__write_context *s)
+{
+   fclose((FILE *)s->context);
+}
+
+#endif // !STBI_WRITE_NO_STDIO
+
+typedef unsigned int stbiw_uint32;
+typedef int stb_image_write_test[sizeof(stbiw_uint32)==4 ? 1 : -1];
+
+static void stbiw__writefv(stbi__write_context *s, const char *fmt, va_list v)
+{
+   while (*fmt) {
+      switch (*fmt++) {
+         case ' ': break;
+         case '1': { unsigned char x = STBIW_UCHAR(va_arg(v, int));
+                     s->func(s->context,&x,1);
+                     break; }
+         case '2': { int x = va_arg(v,int);
+                     unsigned char b[2];
+                     b[0] = STBIW_UCHAR(x);
+                     b[1] = STBIW_UCHAR(x>>8);
+                     s->func(s->context,b,2);
+                     break; }
+         case '4': { stbiw_uint32 x = va_arg(v,int);
+                     unsigned char b[4];
+                     b[0]=STBIW_UCHAR(x);
+                     b[1]=STBIW_UCHAR(x>>8);
+                     b[2]=STBIW_UCHAR(x>>16);
+                     b[3]=STBIW_UCHAR(x>>24);
+                     s->func(s->context,b,4);
+                     break; }
+         default:
+            STBIW_ASSERT(0);
+            return;
+      }
+   }
+}
+
+static void stbiw__writef(stbi__write_context *s, const char *fmt, ...)
+{
+   va_list v;
+   va_start(v, fmt);
+   stbiw__writefv(s, fmt, v);
+   va_end(v);
+}
+
+static void stbiw__write_flush(stbi__write_context *s)
+{
+   if (s->buf_used) {
+      s->func(s->context, &s->buffer, s->buf_used);
+      s->buf_used = 0;
+   }
+}
+
+static void stbiw__putc(stbi__write_context *s, unsigned char c)
+{
+   s->func(s->context, &c, 1);
+}
+
+static void stbiw__write1(stbi__write_context *s, unsigned char a)
+{
+   if ((size_t)s->buf_used + 1 > sizeof(s->buffer))
+      stbiw__write_flush(s);
+   s->buffer[s->buf_used++] = a;
+}
+
+static void stbiw__write3(stbi__write_context *s, unsigned char a, unsigned char b, unsigned char c)
+{
+   int n;
+   if ((size_t)s->buf_used + 3 > sizeof(s->buffer))
+      stbiw__write_flush(s);
+   n = s->buf_used;
+   s->buf_used = n+3;
+   s->buffer[n+0] = a;
+   s->buffer[n+1] = b;
+   s->buffer[n+2] = c;
+}
+
+static void stbiw__write_pixel(stbi__write_context *s, int rgb_dir, int comp, int write_alpha, int expand_mono, unsigned char *d)
+{
+   unsigned char bg[3] = { 255, 0, 255}, px[3];
+   int k;
+
+   if (write_alpha < 0)
+      stbiw__write1(s, d[comp - 1]);
+
+   switch (comp) {
+      case 2: // 2 pixels = mono + alpha, alpha is written separately, so same as 1-channel case
+      case 1:
+         if (expand_mono)
+            stbiw__write3(s, d[0], d[0], d[0]); // monochrome bmp
+         else
+            stbiw__write1(s, d[0]);  // monochrome TGA
+         break;
+      case 4:
+         if (!write_alpha) {
+            // composite against pink background
+            for (k = 0; k < 3; ++k)
+               px[k] = bg[k] + ((d[k] - bg[k]) * d[3]) / 255;
+            stbiw__write3(s, px[1 - rgb_dir], px[1], px[1 + rgb_dir]);
+            break;
+         }
+         /* FALLTHROUGH */
+      case 3:
+         stbiw__write3(s, d[1 - rgb_dir], d[1], d[1 + rgb_dir]);
+         break;
+   }
+   if (write_alpha > 0)
+      stbiw__write1(s, d[comp - 1]);
+}
+
+static void stbiw__write_pixels(stbi__write_context *s, int rgb_dir, int vdir, int x, int y, int comp, void *data, int write_alpha, int scanline_pad, int expand_mono)
+{
+   stbiw_uint32 zero = 0;
+   int i,j, j_end;
+
+   if (y <= 0)
+      return;
+
+   if (stbi__flip_vertically_on_write)
+      vdir *= -1;
+
+   if (vdir < 0) {
+      j_end = -1; j = y-1;
+   } else {
+      j_end =  y; j = 0;
+   }
+
+   for (; j != j_end; j += vdir) {
+      for (i=0; i < x; ++i) {
+         unsigned char *d = (unsigned char *) data + (j*x+i)*comp;
+         stbiw__write_pixel(s, rgb_dir, comp, write_alpha, expand_mono, d);
+      }
+      stbiw__write_flush(s);
+      s->func(s->context, &zero, scanline_pad);
+   }
+}
+
+static int stbiw__outfile(stbi__write_context *s, int rgb_dir, int vdir, int x, int y, int comp, int expand_mono, void *data, int alpha, int pad, const char *fmt, ...)
+{
+   if (y < 0 || x < 0) {
+      return 0;
+   } else {
+      va_list v;
+      va_start(v, fmt);
+      stbiw__writefv(s, fmt, v);
+      va_end(v);
+      stbiw__write_pixels(s,rgb_dir,vdir,x,y,comp,data,alpha,pad, expand_mono);
+      return 1;
+   }
+}
+
+static int stbi_write_bmp_core(stbi__write_context *s, int x, int y, int comp, const void *data)
+{
+   if (comp != 4) {
+      // write RGB bitmap
+      int pad = (-x*3) & 3;
+      return stbiw__outfile(s,-1,-1,x,y,comp,1,(void *) data,0,pad,
+              "11 4 22 4" "4 44 22 444444",
+              'B', 'M', 14+40+(x*3+pad)*y, 0,0, 14+40,  // file header
+               40, x,y, 1,24, 0,0,0,0,0,0);             // bitmap header
+   } else {
+      // RGBA bitmaps need a v4 header
+      // use BI_BITFIELDS mode with 32bpp and alpha mask
+      // (straight BI_RGB with alpha mask doesn't work in most readers)
+      return stbiw__outfile(s,-1,-1,x,y,comp,1,(void *)data,1,0,
+         "11 4 22 4" "4 44 22 444444 4444 4 444 444 444 444",
+         'B', 'M', 14+108+x*y*4, 0, 0, 14+108, // file header
+         108, x,y, 1,32, 3,0,0,0,0,0, 0xff0000,0xff00,0xff,0xff000000u, 0, 0,0,0, 0,0,0, 0,0,0, 0,0,0); // bitmap V4 header
+   }
+}
+
+STBIWDEF int stbi_write_bmp_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data)
+{
+   stbi__write_context s = { 0 };
+   stbi__start_write_callbacks(&s, func, context);
+   return stbi_write_bmp_core(&s, x, y, comp, data);
+}
+
+#ifndef STBI_WRITE_NO_STDIO
+STBIWDEF int stbi_write_bmp(char const *filename, int x, int y, int comp, const void *data)
+{
+   stbi__write_context s = { 0 };
+   if (stbi__start_write_file(&s,filename)) {
+      int r = stbi_write_bmp_core(&s, x, y, comp, data);
+      stbi__end_write_file(&s);
+      return r;
+   } else
+      return 0;
+}
+#endif //!STBI_WRITE_NO_STDIO
+
+static int stbi_write_tga_core(stbi__write_context *s, int x, int y, int comp, void *data)
+{
+   int has_alpha = (comp == 2 || comp == 4);
+   int colorbytes = has_alpha ? comp-1 : comp;
+   int format = colorbytes < 2 ? 3 : 2; // 3 color channels (RGB/RGBA) = 2, 1 color channel (Y/YA) = 3
+
+   if (y < 0 || x < 0)
+      return 0;
+
+   if (!stbi_write_tga_with_rle) {
+      return stbiw__outfile(s, -1, -1, x, y, comp, 0, (void *) data, has_alpha, 0,
+         "111 221 2222 11", 0, 0, format, 0, 0, 0, 0, 0, x, y, (colorbytes + has_alpha) * 8, has_alpha * 8);
+   } else {
+      int i,j,k;
+      int jend, jdir;
+
+      stbiw__writef(s, "111 221 2222 11", 0,0,format+8, 0,0,0, 0,0,x,y, (colorbytes + has_alpha) * 8, has_alpha * 8);
+
+      if (stbi__flip_vertically_on_write) {
+         j = 0;
+         jend = y;
+         jdir = 1;
+      } else {
+         j = y-1;
+         jend = -1;
+         jdir = -1;
+      }
+      for (; j != jend; j += jdir) {
+         unsigned char *row = (unsigned char *) data + j * x * comp;
+         int len;
+
+         for (i = 0; i < x; i += len) {
+            unsigned char *begin = row + i * comp;
+            int diff = 1;
+            len = 1;
+
+            if (i < x - 1) {
+               ++len;
+               diff = memcmp(begin, row + (i + 1) * comp, comp);
+               if (diff) {
+                  const unsigned char *prev = begin;
+                  for (k = i + 2; k < x && len < 128; ++k) {
+                     if (memcmp(prev, row + k * comp, comp)) {
+                        prev += comp;
+                        ++len;
+                     } else {
+                        --len;
+                        break;
+                     }
+                  }
+               } else {
+                  for (k = i + 2; k < x && len < 128; ++k) {
+                     if (!memcmp(begin, row + k * comp, comp)) {
+                        ++len;
+                     } else {
+                        break;
+                     }
+                  }
+               }
+            }
+
+            if (diff) {
+               unsigned char header = STBIW_UCHAR(len - 1);
+               stbiw__write1(s, header);
+               for (k = 0; k < len; ++k) {
+                  stbiw__write_pixel(s, -1, comp, has_alpha, 0, begin + k * comp);
+               }
+            } else {
+               unsigned char header = STBIW_UCHAR(len - 129);
+               stbiw__write1(s, header);
+               stbiw__write_pixel(s, -1, comp, has_alpha, 0, begin);
+            }
+         }
+      }
+      stbiw__write_flush(s);
+   }
+   return 1;
+}
+
+STBIWDEF int stbi_write_tga_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data)
+{
+   stbi__write_context s = { 0 };
+   stbi__start_write_callbacks(&s, func, context);
+   return stbi_write_tga_core(&s, x, y, comp, (void *) data);
+}
+
+#ifndef STBI_WRITE_NO_STDIO
+STBIWDEF int stbi_write_tga(char const *filename, int x, int y, int comp, const void *data)
+{
+   stbi__write_context s = { 0 };
+   if (stbi__start_write_file(&s,filename)) {
+      int r = stbi_write_tga_core(&s, x, y, comp, (void *) data);
+      stbi__end_write_file(&s);
+      return r;
+   } else
+      return 0;
+}
+#endif
+
+// *************************************************************************************************
+// Radiance RGBE HDR writer
+// by Baldur Karlsson
+
+#define stbiw__max(a, b)  ((a) > (b) ? (a) : (b))
+
+#ifndef STBI_WRITE_NO_STDIO
+
+static void stbiw__linear_to_rgbe(unsigned char *rgbe, float *linear)
+{
+   int exponent;
+   float maxcomp = stbiw__max(linear[0], stbiw__max(linear[1], linear[2]));
+
+   if (maxcomp < 1e-32f) {
+      rgbe[0] = rgbe[1] = rgbe[2] = rgbe[3] = 0;
+   } else {
+      float normalize = (float) frexp(maxcomp, &exponent) * 256.0f/maxcomp;
+
+      rgbe[0] = (unsigned char)(linear[0] * normalize);
+      rgbe[1] = (unsigned char)(linear[1] * normalize);
+      rgbe[2] = (unsigned char)(linear[2] * normalize);
+      rgbe[3] = (unsigned char)(exponent + 128);
+   }
+}
+
+static void stbiw__write_run_data(stbi__write_context *s, int length, unsigned char databyte)
+{
+   unsigned char lengthbyte = STBIW_UCHAR(length+128);
+   STBIW_ASSERT(length+128 <= 255);
+   s->func(s->context, &lengthbyte, 1);
+   s->func(s->context, &databyte, 1);
+}
+
+static void stbiw__write_dump_data(stbi__write_context *s, int length, unsigned char *data)
+{
+   unsigned char lengthbyte = STBIW_UCHAR(length);
+   STBIW_ASSERT(length <= 128); // inconsistent with spec but consistent with official code
+   s->func(s->context, &lengthbyte, 1);
+   s->func(s->context, data, length);
+}
+
+static void stbiw__write_hdr_scanline(stbi__write_context *s, int width, int ncomp, unsigned char *scratch, float *scanline)
+{
+   unsigned char scanlineheader[4] = { 2, 2, 0, 0 };
+   unsigned char rgbe[4];
+   float linear[3];
+   int x;
+
+   scanlineheader[2] = (width&0xff00)>>8;
+   scanlineheader[3] = (width&0x00ff);
+
+   /* skip RLE for images too small or large */
+   if (width < 8 || width >= 32768) {
+      for (x=0; x < width; x++) {
+         switch (ncomp) {
+            case 4: /* fallthrough */
+            case 3: linear[2] = scanline[x*ncomp + 2];
+                    linear[1] = scanline[x*ncomp + 1];
+                    linear[0] = scanline[x*ncomp + 0];
+                    break;
+            default:
+                    linear[0] = linear[1] = linear[2] = scanline[x*ncomp + 0];
+                    break;
+         }
+         stbiw__linear_to_rgbe(rgbe, linear);
+         s->func(s->context, rgbe, 4);
+      }
+   } else {
+      int c,r;
+      /* encode into scratch buffer */
+      for (x=0; x < width; x++) {
+         switch(ncomp) {
+            case 4: /* fallthrough */
+            case 3: linear[2] = scanline[x*ncomp + 2];
+                    linear[1] = scanline[x*ncomp + 1];
+                    linear[0] = scanline[x*ncomp + 0];
+                    break;
+            default:
+                    linear[0] = linear[1] = linear[2] = scanline[x*ncomp + 0];
+                    break;
+         }
+         stbiw__linear_to_rgbe(rgbe, linear);
+         scratch[x + width*0] = rgbe[0];
+         scratch[x + width*1] = rgbe[1];
+         scratch[x + width*2] = rgbe[2];
+         scratch[x + width*3] = rgbe[3];
+      }
+
+      s->func(s->context, scanlineheader, 4);
+
+      /* RLE each component separately */
+      for (c=0; c < 4; c++) {
+         unsigned char *comp = &scratch[width*c];
+
+         x = 0;
+         while (x < width) {
+            // find first run
+            r = x;
+            while (r+2 < width) {
+               if (comp[r] == comp[r+1] && comp[r] == comp[r+2])
+                  break;
+               ++r;
+            }
+            if (r+2 >= width)
+               r = width;
+            // dump up to first run
+            while (x < r) {
+               int len = r-x;
+               if (len > 128) len = 128;
+               stbiw__write_dump_data(s, len, &comp[x]);
+               x += len;
+            }
+            // if there's a run, output it
+            if (r+2 < width) { // same test as what we break out of in search loop, so only true if we break'd
+               // find next byte after run
+               while (r < width && comp[r] == comp[x])
+                  ++r;
+               // output run up to r
+               while (x < r) {
+                  int len = r-x;
+                  if (len > 127) len = 127;
+                  stbiw__write_run_data(s, len, comp[x]);
+                  x += len;
+               }
+            }
+         }
+      }
+   }
+}
+
+static int stbi_write_hdr_core(stbi__write_context *s, int x, int y, int comp, float *data)
+{
+   if (y <= 0 || x <= 0 || data == NULL)
+      return 0;
+   else {
+      // Each component is stored separately. Allocate scratch space for full output scanline.
+      unsigned char *scratch = (unsigned char *) STBIW_MALLOC(x*4);
+      int i, len;
+      char buffer[128];
+      char header[] = "#?RADIANCE\n# Written by stb_image_write.h\nFORMAT=32-bit_rle_rgbe\n";
+      s->func(s->context, header, sizeof(header)-1);
+
+#ifdef __STDC_LIB_EXT1__
+      len = sprintf_s(buffer, sizeof(buffer), "EXPOSURE=          1.0000000000000\n\n-Y %d +X %d\n", y, x);
+#else
+      len = sprintf(buffer, "EXPOSURE=          1.0000000000000\n\n-Y %d +X %d\n", y, x);
+#endif
+      s->func(s->context, buffer, len);
+
+      for(i=0; i < y; i++)
+         stbiw__write_hdr_scanline(s, x, comp, scratch, data + comp*x*(stbi__flip_vertically_on_write ? y-1-i : i));
+      STBIW_FREE(scratch);
+      return 1;
+   }
+}
+
+STBIWDEF int stbi_write_hdr_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const float *data)
+{
+   stbi__write_context s = { 0 };
+   stbi__start_write_callbacks(&s, func, context);
+   return stbi_write_hdr_core(&s, x, y, comp, (float *) data);
+}
+
+STBIWDEF int stbi_write_hdr(char const *filename, int x, int y, int comp, const float *data)
+{
+   stbi__write_context s = { 0 };
+   if (stbi__start_write_file(&s,filename)) {
+      int r = stbi_write_hdr_core(&s, x, y, comp, (float *) data);
+      stbi__end_write_file(&s);
+      return r;
+   } else
+      return 0;
+}
+#endif // STBI_WRITE_NO_STDIO
+
+
+//////////////////////////////////////////////////////////////////////////////
+//
+// PNG writer
+//
+
+#ifndef STBIW_ZLIB_COMPRESS
+// stretchy buffer; stbiw__sbpush() == vector<>::push_back() -- stbiw__sbcount() == vector<>::size()
+#define stbiw__sbraw(a) ((int *) (void *) (a) - 2)
+#define stbiw__sbm(a)   stbiw__sbraw(a)[0]
+#define stbiw__sbn(a)   stbiw__sbraw(a)[1]
+
+#define stbiw__sbneedgrow(a,n)  ((a)==0 || stbiw__sbn(a)+n >= stbiw__sbm(a))
+#define stbiw__sbmaybegrow(a,n) (stbiw__sbneedgrow(a,(n)) ? stbiw__sbgrow(a,n) : 0)
+#define stbiw__sbgrow(a,n)  stbiw__sbgrowf((void **) &(a), (n), sizeof(*(a)))
+
+#define stbiw__sbpush(a, v)      (stbiw__sbmaybegrow(a,1), (a)[stbiw__sbn(a)++] = (v))
+#define stbiw__sbcount(a)        ((a) ? stbiw__sbn(a) : 0)
+#define stbiw__sbfree(a)         ((a) ? STBIW_FREE(stbiw__sbraw(a)),0 : 0)
+
+static void *stbiw__sbgrowf(void **arr, int increment, int itemsize)
+{
+   int m = *arr ? 2*stbiw__sbm(*arr)+increment : increment+1;
+   void *p = STBIW_REALLOC_SIZED(*arr ? stbiw__sbraw(*arr) : 0, *arr ? (stbiw__sbm(*arr)*itemsize + sizeof(int)*2) : 0, itemsize * m + sizeof(int)*2);
+   STBIW_ASSERT(p);
+   if (p) {
+      if (!*arr) ((int *) p)[1] = 0;
+      *arr = (void *) ((int *) p + 2);
+      stbiw__sbm(*arr) = m;
+   }
+   return *arr;
+}
+
+static unsigned char *stbiw__zlib_flushf(unsigned char *data, unsigned int *bitbuffer, int *bitcount)
+{
+   while (*bitcount >= 8) {
+      stbiw__sbpush(data, STBIW_UCHAR(*bitbuffer));
+      *bitbuffer >>= 8;
+      *bitcount -= 8;
+   }
+   return data;
+}
+
+static int stbiw__zlib_bitrev(int code, int codebits)
+{
+   int res=0;
+   while (codebits--) {
+      res = (res << 1) | (code & 1);
+      code >>= 1;
+   }
+   return res;
+}
+
+static unsigned int stbiw__zlib_countm(unsigned char *a, unsigned char *b, int limit)
+{
+   int i;
+   for (i=0; i < limit && i < 258; ++i)
+      if (a[i] != b[i]) break;
+   return i;
+}
+
+static unsigned int stbiw__zhash(unsigned char *data)
+{
+   stbiw_uint32 hash = data[0] + (data[1] << 8) + (data[2] << 16);
+   hash ^= hash << 3;
+   hash += hash >> 5;
+   hash ^= hash << 4;
+   hash += hash >> 17;
+   hash ^= hash << 25;
+   hash += hash >> 6;
+   return hash;
+}
+
+#define stbiw__zlib_flush() (out = stbiw__zlib_flushf(out, &bitbuf, &bitcount))
+#define stbiw__zlib_add(code,codebits) \
+      (bitbuf |= (code) << bitcount, bitcount += (codebits), stbiw__zlib_flush())
+#define stbiw__zlib_huffa(b,c)  stbiw__zlib_add(stbiw__zlib_bitrev(b,c),c)
+// default huffman tables
+#define stbiw__zlib_huff1(n)  stbiw__zlib_huffa(0x30 + (n), 8)
+#define stbiw__zlib_huff2(n)  stbiw__zlib_huffa(0x190 + (n)-144, 9)
+#define stbiw__zlib_huff3(n)  stbiw__zlib_huffa(0 + (n)-256,7)
+#define stbiw__zlib_huff4(n)  stbiw__zlib_huffa(0xc0 + (n)-280,8)
+#define stbiw__zlib_huff(n)  ((n) <= 143 ? stbiw__zlib_huff1(n) : (n) <= 255 ? stbiw__zlib_huff2(n) : (n) <= 279 ? stbiw__zlib_huff3(n) : stbiw__zlib_huff4(n))
+#define stbiw__zlib_huffb(n) ((n) <= 143 ? stbiw__zlib_huff1(n) : stbiw__zlib_huff2(n))
+
+#define stbiw__ZHASH   16384
+
+#endif // STBIW_ZLIB_COMPRESS
+
+STBIWDEF unsigned char * stbi_zlib_compress(unsigned char *data, int data_len, int *out_len, int quality)
+{
+#ifdef STBIW_ZLIB_COMPRESS
+   // user provided a zlib compress implementation, use that
+   return STBIW_ZLIB_COMPRESS(data, data_len, out_len, quality);
+#else // use builtin
+   static unsigned short lengthc[] = { 3,4,5,6,7,8,9,10,11,13,15,17,19,23,27,31,35,43,51,59,67,83,99,115,131,163,195,227,258, 259 };
+   static unsigned char  lengtheb[]= { 0,0,0,0,0,0,0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4,  4,  5,  5,  5,  5,  0 };
+   static unsigned short distc[]   = { 1,2,3,4,5,7,9,13,17,25,33,49,65,97,129,193,257,385,513,769,1025,1537,2049,3073,4097,6145,8193,12289,16385,24577, 32768 };
+   static unsigned char  disteb[]  = { 0,0,0,0,1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13 };
+   unsigned int bitbuf=0;
+   int i,j, bitcount=0;
+   unsigned char *out = NULL;
+   unsigned char ***hash_table = (unsigned char***) STBIW_MALLOC(stbiw__ZHASH * sizeof(unsigned char**));
+   if (hash_table == NULL)
+      return NULL;
+   if (quality < 5) quality = 5;
+
+   stbiw__sbpush(out, 0x78);   // DEFLATE 32K window
+   stbiw__sbpush(out, 0x5e);   // FLEVEL = 1
+   stbiw__zlib_add(1,1);  // BFINAL = 1
+   stbiw__zlib_add(1,2);  // BTYPE = 1 -- fixed huffman
+
+   for (i=0; i < stbiw__ZHASH; ++i)
+      hash_table[i] = NULL;
+
+   i=0;
+   while (i < data_len-3) {
+      // hash next 3 bytes of data to be compressed
+      int h = stbiw__zhash(data+i)&(stbiw__ZHASH-1), best=3;
+      unsigned char *bestloc = 0;
+      unsigned char **hlist = hash_table[h];
+      int n = stbiw__sbcount(hlist);
+      for (j=0; j < n; ++j) {
+         if (hlist[j]-data > i-32768) { // if entry lies within window
+            int d = stbiw__zlib_countm(hlist[j], data+i, data_len-i);
+            if (d >= best) { best=d; bestloc=hlist[j]; }
+         }
+      }
+      // when hash table entry is too long, delete half the entries
+      if (hash_table[h] && stbiw__sbn(hash_table[h]) == 2*quality) {
+         STBIW_MEMMOVE(hash_table[h], hash_table[h]+quality, sizeof(hash_table[h][0])*quality);
+         stbiw__sbn(hash_table[h]) = quality;
+      }
+      stbiw__sbpush(hash_table[h],data+i);
+
+      if (bestloc) {
+         // "lazy matching" - check match at *next* byte, and if it's better, do cur byte as literal
+         h = stbiw__zhash(data+i+1)&(stbiw__ZHASH-1);
+         hlist = hash_table[h];
+         n = stbiw__sbcount(hlist);
+         for (j=0; j < n; ++j) {
+            if (hlist[j]-data > i-32767) {
+               int e = stbiw__zlib_countm(hlist[j], data+i+1, data_len-i-1);
+               if (e > best) { // if next match is better, bail on current match
+                  bestloc = NULL;
+                  break;
+               }
+            }
+         }
+      }
+
+      if (bestloc) {
+         int d = (int) (data+i - bestloc); // distance back
+         STBIW_ASSERT(d <= 32767 && best <= 258);
+         for (j=0; best > lengthc[j+1]-1; ++j);
+         stbiw__zlib_huff(j+257);
+         if (lengtheb[j]) stbiw__zlib_add(best - lengthc[j], lengtheb[j]);
+         for (j=0; d > distc[j+1]-1; ++j);
+         stbiw__zlib_add(stbiw__zlib_bitrev(j,5),5);
+         if (disteb[j]) stbiw__zlib_add(d - distc[j], disteb[j]);
+         i += best;
+      } else {
+         stbiw__zlib_huffb(data[i]);
+         ++i;
+      }
+   }
+   // write out final bytes
+   for (;i < data_len; ++i)
+      stbiw__zlib_huffb(data[i]);
+   stbiw__zlib_huff(256); // end of block
+   // pad with 0 bits to byte boundary
+   while (bitcount)
+      stbiw__zlib_add(0,1);
+
+   for (i=0; i < stbiw__ZHASH; ++i)
+      (void) stbiw__sbfree(hash_table[i]);
+   STBIW_FREE(hash_table);
+
+   // store uncompressed instead if compression was worse
+   if (stbiw__sbn(out) > data_len + 2 + ((data_len+32766)/32767)*5) {
+      stbiw__sbn(out) = 2;  // truncate to DEFLATE 32K window and FLEVEL = 1
+      for (j = 0; j < data_len;) {
+         int blocklen = data_len - j;
+         if (blocklen > 32767) blocklen = 32767;
+         stbiw__sbpush(out, data_len - j == blocklen); // BFINAL = ?, BTYPE = 0 -- no compression
+         stbiw__sbpush(out, STBIW_UCHAR(blocklen)); // LEN
+         stbiw__sbpush(out, STBIW_UCHAR(blocklen >> 8));
+         stbiw__sbpush(out, STBIW_UCHAR(~blocklen)); // NLEN
+         stbiw__sbpush(out, STBIW_UCHAR(~blocklen >> 8));
+         memcpy(out+stbiw__sbn(out), data+j, blocklen);
+         stbiw__sbn(out) += blocklen;
+         j += blocklen;
+      }
+   }
+
+   {
+      // compute adler32 on input
+      unsigned int s1=1, s2=0;
+      int blocklen = (int) (data_len % 5552);
+      j=0;
+      while (j < data_len) {
+         for (i=0; i < blocklen; ++i) { s1 += data[j+i]; s2 += s1; }
+         s1 %= 65521; s2 %= 65521;
+         j += blocklen;
+         blocklen = 5552;
+      }
+      stbiw__sbpush(out, STBIW_UCHAR(s2 >> 8));
+      stbiw__sbpush(out, STBIW_UCHAR(s2));
+      stbiw__sbpush(out, STBIW_UCHAR(s1 >> 8));
+      stbiw__sbpush(out, STBIW_UCHAR(s1));
+   }
+   *out_len = stbiw__sbn(out);
+   // make returned pointer freeable
+   STBIW_MEMMOVE(stbiw__sbraw(out), out, *out_len);
+   return (unsigned char *) stbiw__sbraw(out);
+#endif // STBIW_ZLIB_COMPRESS
+}
+
+static unsigned int stbiw__crc32(unsigned char *buffer, int len)
+{
+#ifdef STBIW_CRC32
+    return STBIW_CRC32(buffer, len);
+#else
+   static unsigned int crc_table[256] =
+   {
+      0x00000000, 0x77073096, 0xEE0E612C, 0x990951BA, 0x076DC419, 0x706AF48F, 0xE963A535, 0x9E6495A3,
+      0x0eDB8832, 0x79DCB8A4, 0xE0D5E91E, 0x97D2D988, 0x09B64C2B, 0x7EB17CBD, 0xE7B82D07, 0x90BF1D91,
+      0x1DB71064, 0x6AB020F2, 0xF3B97148, 0x84BE41DE, 0x1ADAD47D, 0x6DDDE4EB, 0xF4D4B551, 0x83D385C7,
+      0x136C9856, 0x646BA8C0, 0xFD62F97A, 0x8A65C9EC, 0x14015C4F, 0x63066CD9, 0xFA0F3D63, 0x8D080DF5,
+      0x3B6E20C8, 0x4C69105E, 0xD56041E4, 0xA2677172, 0x3C03E4D1, 0x4B04D447, 0xD20D85FD, 0xA50AB56B,
+      0x35B5A8FA, 0x42B2986C, 0xDBBBC9D6, 0xACBCF940, 0x32D86CE3, 0x45DF5C75, 0xDCD60DCF, 0xABD13D59,
+      0x26D930AC, 0x51DE003A, 0xC8D75180, 0xBFD06116, 0x21B4F4B5, 0x56B3C423, 0xCFBA9599, 0xB8BDA50F,
+      0x2802B89E, 0x5F058808, 0xC60CD9B2, 0xB10BE924, 0x2F6F7C87, 0x58684C11, 0xC1611DAB, 0xB6662D3D,
+      0x76DC4190, 0x01DB7106, 0x98D220BC, 0xEFD5102A, 0x71B18589, 0x06B6B51F, 0x9FBFE4A5, 0xE8B8D433,
+      0x7807C9A2, 0x0F00F934, 0x9609A88E, 0xE10E9818, 0x7F6A0DBB, 0x086D3D2D, 0x91646C97, 0xE6635C01,
+      0x6B6B51F4, 0x1C6C6162, 0x856530D8, 0xF262004E, 0x6C0695ED, 0x1B01A57B, 0x8208F4C1, 0xF50FC457,
+      0x65B0D9C6, 0x12B7E950, 0x8BBEB8EA, 0xFCB9887C, 0x62DD1DDF, 0x15DA2D49, 0x8CD37CF3, 0xFBD44C65,
+      0x4DB26158, 0x3AB551CE, 0xA3BC0074, 0xD4BB30E2, 0x4ADFA541, 0x3DD895D7, 0xA4D1C46D, 0xD3D6F4FB,
+      0x4369E96A, 0x346ED9FC, 0xAD678846, 0xDA60B8D0, 0x44042D73, 0x33031DE5, 0xAA0A4C5F, 0xDD0D7CC9,
+      0x5005713C, 0x270241AA, 0xBE0B1010, 0xC90C2086, 0x5768B525, 0x206F85B3, 0xB966D409, 0xCE61E49F,
+      0x5EDEF90E, 0x29D9C998, 0xB0D09822, 0xC7D7A8B4, 0x59B33D17, 0x2EB40D81, 0xB7BD5C3B, 0xC0BA6CAD,
+      0xEDB88320, 0x9ABFB3B6, 0x03B6E20C, 0x74B1D29A, 0xEAD54739, 0x9DD277AF, 0x04DB2615, 0x73DC1683,
+      0xE3630B12, 0x94643B84, 0x0D6D6A3E, 0x7A6A5AA8, 0xE40ECF0B, 0x9309FF9D, 0x0A00AE27, 0x7D079EB1,
+      0xF00F9344, 0x8708A3D2, 0x1E01F268, 0x6906C2FE, 0xF762575D, 0x806567CB, 0x196C3671, 0x6E6B06E7,
+      0xFED41B76, 0x89D32BE0, 0x10DA7A5A, 0x67DD4ACC, 0xF9B9DF6F, 0x8EBEEFF9, 0x17B7BE43, 0x60B08ED5,
+      0xD6D6A3E8, 0xA1D1937E, 0x38D8C2C4, 0x4FDFF252, 0xD1BB67F1, 0xA6BC5767, 0x3FB506DD, 0x48B2364B,
+      0xD80D2BDA, 0xAF0A1B4C, 0x36034AF6, 0x41047A60, 0xDF60EFC3, 0xA867DF55, 0x316E8EEF, 0x4669BE79,
+      0xCB61B38C, 0xBC66831A, 0x256FD2A0, 0x5268E236, 0xCC0C7795, 0xBB0B4703, 0x220216B9, 0x5505262F,
+      0xC5BA3BBE, 0xB2BD0B28, 0x2BB45A92, 0x5CB36A04, 0xC2D7FFA7, 0xB5D0CF31, 0x2CD99E8B, 0x5BDEAE1D,
+      0x9B64C2B0, 0xEC63F226, 0x756AA39C, 0x026D930A, 0x9C0906A9, 0xEB0E363F, 0x72076785, 0x05005713,
+      0x95BF4A82, 0xE2B87A14, 0x7BB12BAE, 0x0CB61B38, 0x92D28E9B, 0xE5D5BE0D, 0x7CDCEFB7, 0x0BDBDF21,
+      0x86D3D2D4, 0xF1D4E242, 0x68DDB3F8, 0x1FDA836E, 0x81BE16CD, 0xF6B9265B, 0x6FB077E1, 0x18B74777,
+      0x88085AE6, 0xFF0F6A70, 0x66063BCA, 0x11010B5C, 0x8F659EFF, 0xF862AE69, 0x616BFFD3, 0x166CCF45,
+      0xA00AE278, 0xD70DD2EE, 0x4E048354, 0x3903B3C2, 0xA7672661, 0xD06016F7, 0x4969474D, 0x3E6E77DB,
+      0xAED16A4A, 0xD9D65ADC, 0x40DF0B66, 0x37D83BF0, 0xA9BCAE53, 0xDEBB9EC5, 0x47B2CF7F, 0x30B5FFE9,
+      0xBDBDF21C, 0xCABAC28A, 0x53B39330, 0x24B4A3A6, 0xBAD03605, 0xCDD70693, 0x54DE5729, 0x23D967BF,
+      0xB3667A2E, 0xC4614AB8, 0x5D681B02, 0x2A6F2B94, 0xB40BBE37, 0xC30C8EA1, 0x5A05DF1B, 0x2D02EF8D
+   };
+
+   unsigned int crc = ~0u;
+   int i;
+   for (i=0; i < len; ++i)
+      crc = (crc >> 8) ^ crc_table[buffer[i] ^ (crc & 0xff)];
+   return ~crc;
+#endif
+}
+
+#define stbiw__wpng4(o,a,b,c,d) ((o)[0]=STBIW_UCHAR(a),(o)[1]=STBIW_UCHAR(b),(o)[2]=STBIW_UCHAR(c),(o)[3]=STBIW_UCHAR(d),(o)+=4)
+#define stbiw__wp32(data,v) stbiw__wpng4(data, (v)>>24,(v)>>16,(v)>>8,(v));
+#define stbiw__wptag(data,s) stbiw__wpng4(data, s[0],s[1],s[2],s[3])
+
+static void stbiw__wpcrc(unsigned char **data, int len)
+{
+   unsigned int crc = stbiw__crc32(*data - len - 4, len+4);
+   stbiw__wp32(*data, crc);
+}
+
+static unsigned char stbiw__paeth(int a, int b, int c)
+{
+   int p = a + b - c, pa = abs(p-a), pb = abs(p-b), pc = abs(p-c);
+   if (pa <= pb && pa <= pc) return STBIW_UCHAR(a);
+   if (pb <= pc) return STBIW_UCHAR(b);
+   return STBIW_UCHAR(c);
+}
+
+// @OPTIMIZE: provide an option that always forces left-predict or paeth predict
+static void stbiw__encode_png_line(unsigned char *pixels, int stride_bytes, int width, int height, int y, int n, int filter_type, signed char *line_buffer)
+{
+   static int mapping[] = { 0,1,2,3,4 };
+   static int firstmap[] = { 0,1,0,5,6 };
+   int *mymap = (y != 0) ? mapping : firstmap;
+   int i;
+   int type = mymap[filter_type];
+   unsigned char *z = pixels + stride_bytes * (stbi__flip_vertically_on_write ? height-1-y : y);
+   int signed_stride = stbi__flip_vertically_on_write ? -stride_bytes : stride_bytes;
+
+   if (type==0) {
+      memcpy(line_buffer, z, width*n);
+      return;
+   }
+
+   // first loop isn't optimized since it's just one pixel
+   for (i = 0; i < n; ++i) {
+      switch (type) {
+         case 1: line_buffer[i] = z[i]; break;
+         case 2: line_buffer[i] = z[i] - z[i-signed_stride]; break;
+         case 3: line_buffer[i] = z[i] - (z[i-signed_stride]>>1); break;
+         case 4: line_buffer[i] = (signed char) (z[i] - stbiw__paeth(0,z[i-signed_stride],0)); break;
+         case 5: line_buffer[i] = z[i]; break;
+         case 6: line_buffer[i] = z[i]; break;
+      }
+   }
+   switch (type) {
+      case 1: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - z[i-n]; break;
+      case 2: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - z[i-signed_stride]; break;
+      case 3: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - ((z[i-n] + z[i-signed_stride])>>1); break;
+      case 4: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - stbiw__paeth(z[i-n], z[i-signed_stride], z[i-signed_stride-n]); break;
+      case 5: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - (z[i-n]>>1); break;
+      case 6: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - stbiw__paeth(z[i-n], 0,0); break;
+   }
+}
+
+STBIWDEF unsigned char *stbi_write_png_to_mem(const unsigned char *pixels, int stride_bytes, int x, int y, int n, int *out_len)
+{
+   int force_filter = stbi_write_force_png_filter;
+   int ctype[5] = { -1, 0, 4, 2, 6 };
+   unsigned char sig[8] = { 137,80,78,71,13,10,26,10 };
+   unsigned char *out,*o, *filt, *zlib;
+   signed char *line_buffer;
+   int j,zlen;
+
+   if (stride_bytes == 0)
+      stride_bytes = x * n;
+
+   if (force_filter >= 5) {
+      force_filter = -1;
+   }
+
+   filt = (unsigned char *) STBIW_MALLOC((x*n+1) * y); if (!filt) return 0;
+   line_buffer = (signed char *) STBIW_MALLOC(x * n); if (!line_buffer) { STBIW_FREE(filt); return 0; }
+   for (j=0; j < y; ++j) {
+      int filter_type;
+      if (force_filter > -1) {
+         filter_type = force_filter;
+         stbiw__encode_png_line((unsigned char*)(pixels), stride_bytes, x, y, j, n, force_filter, line_buffer);
+      } else { // Estimate the best filter by running through all of them:
+         int best_filter = 0, best_filter_val = 0x7fffffff, est, i;
+         for (filter_type = 0; filter_type < 5; filter_type++) {
+            stbiw__encode_png_line((unsigned char*)(pixels), stride_bytes, x, y, j, n, filter_type, line_buffer);
+
+            // Estimate the entropy of the line using this filter; the less, the better.
+            est = 0;
+            for (i = 0; i < x*n; ++i) {
+               est += abs((signed char) line_buffer[i]);
+            }
+            if (est < best_filter_val) {
+               best_filter_val = est;
+               best_filter = filter_type;
+            }
+         }
+         if (filter_type != best_filter) {  // If the last iteration already got us the best filter, don't redo it
+            stbiw__encode_png_line((unsigned char*)(pixels), stride_bytes, x, y, j, n, best_filter, line_buffer);
+            filter_type = best_filter;
+         }
+      }
+      // when we get here, filter_type contains the filter type, and line_buffer contains the data
+      filt[j*(x*n+1)] = (unsigned char) filter_type;
+      STBIW_MEMMOVE(filt+j*(x*n+1)+1, line_buffer, x*n);
+   }
+   STBIW_FREE(line_buffer);
+   zlib = stbi_zlib_compress(filt, y*( x*n+1), &zlen, stbi_write_png_compression_level);
+   STBIW_FREE(filt);
+   if (!zlib) return 0;
+
+   // each tag requires 12 bytes of overhead
+   out = (unsigned char *) STBIW_MALLOC(8 + 12+13 + 12+zlen + 12);
+   if (!out) return 0;
+   *out_len = 8 + 12+13 + 12+zlen + 12;
+
+   o=out;
+   STBIW_MEMMOVE(o,sig,8); o+= 8;
+   stbiw__wp32(o, 13); // header length
+   stbiw__wptag(o, "IHDR");
+   stbiw__wp32(o, x);
+   stbiw__wp32(o, y);
+   *o++ = 8;
+   *o++ = STBIW_UCHAR(ctype[n]);
+   *o++ = 0;
+   *o++ = 0;
+   *o++ = 0;
+   stbiw__wpcrc(&o,13);
+
+   stbiw__wp32(o, zlen);
+   stbiw__wptag(o, "IDAT");
+   STBIW_MEMMOVE(o, zlib, zlen);
+   o += zlen;
+   STBIW_FREE(zlib);
+   stbiw__wpcrc(&o, zlen);
+
+   stbiw__wp32(o,0);
+   stbiw__wptag(o, "IEND");
+   stbiw__wpcrc(&o,0);
+
+   STBIW_ASSERT(o == out + *out_len);
+
+   return out;
+}
+
+#ifndef STBI_WRITE_NO_STDIO
+STBIWDEF int stbi_write_png(char const *filename, int x, int y, int comp, const void *data, int stride_bytes)
+{
+   FILE *f;
+   int len;
+   unsigned char *png = stbi_write_png_to_mem((const unsigned char *) data, stride_bytes, x, y, comp, &len);
+   if (png == NULL) return 0;
+
+   f = stbiw__fopen(filename, "wb");
+   if (!f) { STBIW_FREE(png); return 0; }
+   fwrite(png, 1, len, f);
+   fclose(f);
+   STBIW_FREE(png);
+   return 1;
+}
+#endif
+
+STBIWDEF int stbi_write_png_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data, int stride_bytes)
+{
+   int len;
+   unsigned char *png = stbi_write_png_to_mem((const unsigned char *) data, stride_bytes, x, y, comp, &len);
+   if (png == NULL) return 0;
+   func(context, png, len);
+   STBIW_FREE(png);
+   return 1;
+}
+
+
+/* ***************************************************************************
+ *
+ * JPEG writer
+ *
+ * This is based on Jon Olick's jo_jpeg.cpp:
+ * public domain Simple, Minimalistic JPEG writer - http://www.jonolick.com/code.html
+ */
+
+static const unsigned char stbiw__jpg_ZigZag[] = { 0,1,5,6,14,15,27,28,2,4,7,13,16,26,29,42,3,8,12,17,25,30,41,43,9,11,18,
+      24,31,40,44,53,10,19,23,32,39,45,52,54,20,22,33,38,46,51,55,60,21,34,37,47,50,56,59,61,35,36,48,49,57,58,62,63 };
+
+static void stbiw__jpg_writeBits(stbi__write_context *s, int *bitBufP, int *bitCntP, const unsigned short *bs) {
+   int bitBuf = *bitBufP, bitCnt = *bitCntP;
+   bitCnt += bs[1];
+   bitBuf |= bs[0] << (24 - bitCnt);
+   while(bitCnt >= 8) {
+      unsigned char c = (bitBuf >> 16) & 255;
+      stbiw__putc(s, c);
+      if(c == 255) {
+         stbiw__putc(s, 0);
+      }
+      bitBuf <<= 8;
+      bitCnt -= 8;
+   }
+   *bitBufP = bitBuf;
+   *bitCntP = bitCnt;
+}
+
+static void stbiw__jpg_DCT(float *d0p, float *d1p, float *d2p, float *d3p, float *d4p, float *d5p, float *d6p, float *d7p) {
+   float d0 = *d0p, d1 = *d1p, d2 = *d2p, d3 = *d3p, d4 = *d4p, d5 = *d5p, d6 = *d6p, d7 = *d7p;
+   float z1, z2, z3, z4, z5, z11, z13;
+
+   float tmp0 = d0 + d7;
+   float tmp7 = d0 - d7;
+   float tmp1 = d1 + d6;
+   float tmp6 = d1 - d6;
+   float tmp2 = d2 + d5;
+   float tmp5 = d2 - d5;
+   float tmp3 = d3 + d4;
+   float tmp4 = d3 - d4;
+
+   // Even part
+   float tmp10 = tmp0 + tmp3;   // phase 2
+   float tmp13 = tmp0 - tmp3;
+   float tmp11 = tmp1 + tmp2;
+   float tmp12 = tmp1 - tmp2;
+
+   d0 = tmp10 + tmp11;       // phase 3
+   d4 = tmp10 - tmp11;
+
+   z1 = (tmp12 + tmp13) * 0.707106781f; // c4
+   d2 = tmp13 + z1;       // phase 5
+   d6 = tmp13 - z1;
+
+   // Odd part
+   tmp10 = tmp4 + tmp5;       // phase 2
+   tmp11 = tmp5 + tmp6;
+   tmp12 = tmp6 + tmp7;
+
+   // The rotator is modified from fig 4-8 to avoid extra negations.
+   z5 = (tmp10 - tmp12) * 0.382683433f; // c6
+   z2 = tmp10 * 0.541196100f + z5; // c2-c6
+   z4 = tmp12 * 1.306562965f + z5; // c2+c6
+   z3 = tmp11 * 0.707106781f; // c4
+
+   z11 = tmp7 + z3;      // phase 5
+   z13 = tmp7 - z3;
+
+   *d5p = z13 + z2;         // phase 6
+   *d3p = z13 - z2;
+   *d1p = z11 + z4;
+   *d7p = z11 - z4;
+
+   *d0p = d0;  *d2p = d2;  *d4p = d4;  *d6p = d6;
+}
+
+static void stbiw__jpg_calcBits(int val, unsigned short bits[2]) {
+   int tmp1 = val < 0 ? -val : val;
+   val = val < 0 ? val-1 : val;
+   bits[1] = 1;
+   while(tmp1 >>= 1) {
+      ++bits[1];
+   }
+   bits[0] = val & ((1<<bits[1])-1);
+}
+
+static int stbiw__jpg_processDU(stbi__write_context *s, int *bitBuf, int *bitCnt, float *CDU, int du_stride, float *fdtbl, int DC, const unsigned short HTDC[256][2], const unsigned short HTAC[256][2]) {
+   const unsigned short EOB[2] = { HTAC[0x00][0], HTAC[0x00][1] };
+   const unsigned short M16zeroes[2] = { HTAC[0xF0][0], HTAC[0xF0][1] };
+   int dataOff, i, j, n, diff, end0pos, x, y;
+   int DU[64];
+
+   // DCT rows
+   for(dataOff=0, n=du_stride*8; dataOff<n; dataOff+=du_stride) {
+      stbiw__jpg_DCT(&CDU[dataOff], &CDU[dataOff+1], &CDU[dataOff+2], &CDU[dataOff+3], &CDU[dataOff+4], &CDU[dataOff+5], &CDU[dataOff+6], &CDU[dataOff+7]);
+   }
+   // DCT columns
+   for(dataOff=0; dataOff<8; ++dataOff) {
+      stbiw__jpg_DCT(&CDU[dataOff], &CDU[dataOff+du_stride], &CDU[dataOff+du_stride*2], &CDU[dataOff+du_stride*3], &CDU[dataOff+du_stride*4],
+                     &CDU[dataOff+du_stride*5], &CDU[dataOff+du_stride*6], &CDU[dataOff+du_stride*7]);
+   }
+   // Quantize/descale/zigzag the coefficients
+   for(y = 0, j=0; y < 8; ++y) {
+      for(x = 0; x < 8; ++x,++j) {
+         float v;
+         i = y*du_stride+x;
+         v = CDU[i]*fdtbl[j];
+         // DU[stbiw__jpg_ZigZag[j]] = (int)(v < 0 ? ceilf(v - 0.5f) : floorf(v + 0.5f));
+         // ceilf() and floorf() are C99, not C89, but I /think/ they're not needed here anyway?
+         DU[stbiw__jpg_ZigZag[j]] = (int)(v < 0 ? v - 0.5f : v + 0.5f);
+      }
+   }
+
+   // Encode DC
+   diff = DU[0] - DC;
+   if (diff == 0) {
+      stbiw__jpg_writeBits(s, bitBuf, bitCnt, HTDC[0]);
+   } else {
+      unsigned short bits[2];
+      stbiw__jpg_calcBits(diff, bits);
+      stbiw__jpg_writeBits(s, bitBuf, bitCnt, HTDC[bits[1]]);
+      stbiw__jpg_writeBits(s, bitBuf, bitCnt, bits);
+   }
+   // Encode ACs
+   end0pos = 63;
+   for(; (end0pos>0)&&(DU[end0pos]==0); --end0pos) {
+   }
+   // end0pos = first element in reverse order !=0
+   if(end0pos == 0) {
+      stbiw__jpg_writeBits(s, bitBuf, bitCnt, EOB);
+      return DU[0];
+   }
+   for(i = 1; i <= end0pos; ++i) {
+      int startpos = i;
+      int nrzeroes;
+      unsigned short bits[2];
+      for (; DU[i]==0 && i<=end0pos; ++i) {
+      }
+      nrzeroes = i-startpos;
+      if ( nrzeroes >= 16 ) {
+         int lng = nrzeroes>>4;
+         int nrmarker;
+         for (nrmarker=1; nrmarker <= lng; ++nrmarker)
+            stbiw__jpg_writeBits(s, bitBuf, bitCnt, M16zeroes);
+         nrzeroes &= 15;
+      }
+      stbiw__jpg_calcBits(DU[i], bits);
+      stbiw__jpg_writeBits(s, bitBuf, bitCnt, HTAC[(nrzeroes<<4)+bits[1]]);
+      stbiw__jpg_writeBits(s, bitBuf, bitCnt, bits);
+   }
+   if(end0pos != 63) {
+      stbiw__jpg_writeBits(s, bitBuf, bitCnt, EOB);
+   }
+   return DU[0];
+}
+
+static int stbi_write_jpg_core(stbi__write_context *s, int width, int height, int comp, const void* data, int quality) {
+   // Constants that don't pollute global namespace
+   static const unsigned char std_dc_luminance_nrcodes[] = {0,0,1,5,1,1,1,1,1,1,0,0,0,0,0,0,0};
+   static const unsigned char std_dc_luminance_values[] = {0,1,2,3,4,5,6,7,8,9,10,11};
+   static const unsigned char std_ac_luminance_nrcodes[] = {0,0,2,1,3,3,2,4,3,5,5,4,4,0,0,1,0x7d};
+   static const unsigned char std_ac_luminance_values[] = {
+      0x01,0x02,0x03,0x00,0x04,0x11,0x05,0x12,0x21,0x31,0x41,0x06,0x13,0x51,0x61,0x07,0x22,0x71,0x14,0x32,0x81,0x91,0xa1,0x08,
+      0x23,0x42,0xb1,0xc1,0x15,0x52,0xd1,0xf0,0x24,0x33,0x62,0x72,0x82,0x09,0x0a,0x16,0x17,0x18,0x19,0x1a,0x25,0x26,0x27,0x28,
+      0x29,0x2a,0x34,0x35,0x36,0x37,0x38,0x39,0x3a,0x43,0x44,0x45,0x46,0x47,0x48,0x49,0x4a,0x53,0x54,0x55,0x56,0x57,0x58,0x59,
+      0x5a,0x63,0x64,0x65,0x66,0x67,0x68,0x69,0x6a,0x73,0x74,0x75,0x76,0x77,0x78,0x79,0x7a,0x83,0x84,0x85,0x86,0x87,0x88,0x89,
+      0x8a,0x92,0x93,0x94,0x95,0x96,0x97,0x98,0x99,0x9a,0xa2,0xa3,0xa4,0xa5,0xa6,0xa7,0xa8,0xa9,0xaa,0xb2,0xb3,0xb4,0xb5,0xb6,
+      0xb7,0xb8,0xb9,0xba,0xc2,0xc3,0xc4,0xc5,0xc6,0xc7,0xc8,0xc9,0xca,0xd2,0xd3,0xd4,0xd5,0xd6,0xd7,0xd8,0xd9,0xda,0xe1,0xe2,
+      0xe3,0xe4,0xe5,0xe6,0xe7,0xe8,0xe9,0xea,0xf1,0xf2,0xf3,0xf4,0xf5,0xf6,0xf7,0xf8,0xf9,0xfa
+   };
+   static const unsigned char std_dc_chrominance_nrcodes[] = {0,0,3,1,1,1,1,1,1,1,1,1,0,0,0,0,0};
+   static const unsigned char std_dc_chrominance_values[] = {0,1,2,3,4,5,6,7,8,9,10,11};
+   static const unsigned char std_ac_chrominance_nrcodes[] = {0,0,2,1,2,4,4,3,4,7,5,4,4,0,1,2,0x77};
+   static const unsigned char std_ac_chrominance_values[] = {
+      0x00,0x01,0x02,0x03,0x11,0x04,0x05,0x21,0x31,0x06,0x12,0x41,0x51,0x07,0x61,0x71,0x13,0x22,0x32,0x81,0x08,0x14,0x42,0x91,
+      0xa1,0xb1,0xc1,0x09,0x23,0x33,0x52,0xf0,0x15,0x62,0x72,0xd1,0x0a,0x16,0x24,0x34,0xe1,0x25,0xf1,0x17,0x18,0x19,0x1a,0x26,
+      0x27,0x28,0x29,0x2a,0x35,0x36,0x37,0x38,0x39,0x3a,0x43,0x44,0x45,0x46,0x47,0x48,0x49,0x4a,0x53,0x54,0x55,0x56,0x57,0x58,
+      0x59,0x5a,0x63,0x64,0x65,0x66,0x67,0x68,0x69,0x6a,0x73,0x74,0x75,0x76,0x77,0x78,0x79,0x7a,0x82,0x83,0x84,0x85,0x86,0x87,
+      0x88,0x89,0x8a,0x92,0x93,0x94,0x95,0x96,0x97,0x98,0x99,0x9a,0xa2,0xa3,0xa4,0xa5,0xa6,0xa7,0xa8,0xa9,0xaa,0xb2,0xb3,0xb4,
+      0xb5,0xb6,0xb7,0xb8,0xb9,0xba,0xc2,0xc3,0xc4,0xc5,0xc6,0xc7,0xc8,0xc9,0xca,0xd2,0xd3,0xd4,0xd5,0xd6,0xd7,0xd8,0xd9,0xda,
+      0xe2,0xe3,0xe4,0xe5,0xe6,0xe7,0xe8,0xe9,0xea,0xf2,0xf3,0xf4,0xf5,0xf6,0xf7,0xf8,0xf9,0xfa
+   };
+   // Huffman tables
+   static const unsigned short YDC_HT[256][2] = { {0,2},{2,3},{3,3},{4,3},{5,3},{6,3},{14,4},{30,5},{62,6},{126,7},{254,8},{510,9}};
+   static const unsigned short UVDC_HT[256][2] = { {0,2},{1,2},{2,2},{6,3},{14,4},{30,5},{62,6},{126,7},{254,8},{510,9},{1022,10},{2046,11}};
+   static const unsigned short YAC_HT[256][2] = {
+      {10,4},{0,2},{1,2},{4,3},{11,4},{26,5},{120,7},{248,8},{1014,10},{65410,16},{65411,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {12,4},{27,5},{121,7},{502,9},{2038,11},{65412,16},{65413,16},{65414,16},{65415,16},{65416,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {28,5},{249,8},{1015,10},{4084,12},{65417,16},{65418,16},{65419,16},{65420,16},{65421,16},{65422,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {58,6},{503,9},{4085,12},{65423,16},{65424,16},{65425,16},{65426,16},{65427,16},{65428,16},{65429,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {59,6},{1016,10},{65430,16},{65431,16},{65432,16},{65433,16},{65434,16},{65435,16},{65436,16},{65437,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {122,7},{2039,11},{65438,16},{65439,16},{65440,16},{65441,16},{65442,16},{65443,16},{65444,16},{65445,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {123,7},{4086,12},{65446,16},{65447,16},{65448,16},{65449,16},{65450,16},{65451,16},{65452,16},{65453,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {250,8},{4087,12},{65454,16},{65455,16},{65456,16},{65457,16},{65458,16},{65459,16},{65460,16},{65461,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {504,9},{32704,15},{65462,16},{65463,16},{65464,16},{65465,16},{65466,16},{65467,16},{65468,16},{65469,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {505,9},{65470,16},{65471,16},{65472,16},{65473,16},{65474,16},{65475,16},{65476,16},{65477,16},{65478,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {506,9},{65479,16},{65480,16},{65481,16},{65482,16},{65483,16},{65484,16},{65485,16},{65486,16},{65487,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {1017,10},{65488,16},{65489,16},{65490,16},{65491,16},{65492,16},{65493,16},{65494,16},{65495,16},{65496,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {1018,10},{65497,16},{65498,16},{65499,16},{65500,16},{65501,16},{65502,16},{65503,16},{65504,16},{65505,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {2040,11},{65506,16},{65507,16},{65508,16},{65509,16},{65510,16},{65511,16},{65512,16},{65513,16},{65514,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {65515,16},{65516,16},{65517,16},{65518,16},{65519,16},{65520,16},{65521,16},{65522,16},{65523,16},{65524,16},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {2041,11},{65525,16},{65526,16},{65527,16},{65528,16},{65529,16},{65530,16},{65531,16},{65532,16},{65533,16},{65534,16},{0,0},{0,0},{0,0},{0,0},{0,0}
+   };
+   static const unsigned short UVAC_HT[256][2] = {
+      {0,2},{1,2},{4,3},{10,4},{24,5},{25,5},{56,6},{120,7},{500,9},{1014,10},{4084,12},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {11,4},{57,6},{246,8},{501,9},{2038,11},{4085,12},{65416,16},{65417,16},{65418,16},{65419,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {26,5},{247,8},{1015,10},{4086,12},{32706,15},{65420,16},{65421,16},{65422,16},{65423,16},{65424,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {27,5},{248,8},{1016,10},{4087,12},{65425,16},{65426,16},{65427,16},{65428,16},{65429,16},{65430,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {58,6},{502,9},{65431,16},{65432,16},{65433,16},{65434,16},{65435,16},{65436,16},{65437,16},{65438,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {59,6},{1017,10},{65439,16},{65440,16},{65441,16},{65442,16},{65443,16},{65444,16},{65445,16},{65446,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {121,7},{2039,11},{65447,16},{65448,16},{65449,16},{65450,16},{65451,16},{65452,16},{65453,16},{65454,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {122,7},{2040,11},{65455,16},{65456,16},{65457,16},{65458,16},{65459,16},{65460,16},{65461,16},{65462,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {249,8},{65463,16},{65464,16},{65465,16},{65466,16},{65467,16},{65468,16},{65469,16},{65470,16},{65471,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {503,9},{65472,16},{65473,16},{65474,16},{65475,16},{65476,16},{65477,16},{65478,16},{65479,16},{65480,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {504,9},{65481,16},{65482,16},{65483,16},{65484,16},{65485,16},{65486,16},{65487,16},{65488,16},{65489,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {505,9},{65490,16},{65491,16},{65492,16},{65493,16},{65494,16},{65495,16},{65496,16},{65497,16},{65498,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {506,9},{65499,16},{65500,16},{65501,16},{65502,16},{65503,16},{65504,16},{65505,16},{65506,16},{65507,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {2041,11},{65508,16},{65509,16},{65510,16},{65511,16},{65512,16},{65513,16},{65514,16},{65515,16},{65516,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {16352,14},{65517,16},{65518,16},{65519,16},{65520,16},{65521,16},{65522,16},{65523,16},{65524,16},{65525,16},{0,0},{0,0},{0,0},{0,0},{0,0},
+      {1018,10},{32707,15},{65526,16},{65527,16},{65528,16},{65529,16},{65530,16},{65531,16},{65532,16},{65533,16},{65534,16},{0,0},{0,0},{0,0},{0,0},{0,0}
+   };
+   static const int YQT[] = {16,11,10,16,24,40,51,61,12,12,14,19,26,58,60,55,14,13,16,24,40,57,69,56,14,17,22,29,51,87,80,62,18,22,
+                             37,56,68,109,103,77,24,35,55,64,81,104,113,92,49,64,78,87,103,121,120,101,72,92,95,98,112,100,103,99};
+   static const int UVQT[] = {17,18,24,47,99,99,99,99,18,21,26,66,99,99,99,99,24,26,56,99,99,99,99,99,47,66,99,99,99,99,99,99,
+                              99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99};
+   static const float aasf[] = { 1.0f * 2.828427125f, 1.387039845f * 2.828427125f, 1.306562965f * 2.828427125f, 1.175875602f * 2.828427125f,
+                                 1.0f * 2.828427125f, 0.785694958f * 2.828427125f, 0.541196100f * 2.828427125f, 0.275899379f * 2.828427125f };
+
+   int row, col, i, k, subsample;
+   float fdtbl_Y[64], fdtbl_UV[64];
+   unsigned char YTable[64], UVTable[64];
+
+   if(!data || !width || !height || comp > 4 || comp < 1) {
+      return 0;
+   }
+
+   quality = quality ? quality : 90;
+   subsample = quality <= 90 ? 1 : 0;
+   quality = quality < 1 ? 1 : quality > 100 ? 100 : quality;
+   quality = quality < 50 ? 5000 / quality : 200 - quality * 2;
+
+   for(i = 0; i < 64; ++i) {
+      int uvti, yti = (YQT[i]*quality+50)/100;
+      YTable[stbiw__jpg_ZigZag[i]] = (unsigned char) (yti < 1 ? 1 : yti > 255 ? 255 : yti);
+      uvti = (UVQT[i]*quality+50)/100;
+      UVTable[stbiw__jpg_ZigZag[i]] = (unsigned char) (uvti < 1 ? 1 : uvti > 255 ? 255 : uvti);
+   }
+
+   for(row = 0, k = 0; row < 8; ++row) {
+      for(col = 0; col < 8; ++col, ++k) {
+         fdtbl_Y[k]  = 1 / (YTable [stbiw__jpg_ZigZag[k]] * aasf[row] * aasf[col]);
+         fdtbl_UV[k] = 1 / (UVTable[stbiw__jpg_ZigZag[k]] * aasf[row] * aasf[col]);
+      }
+   }
+
+   // Write Headers
+   {
+      static const unsigned char head0[] = { 0xFF,0xD8,0xFF,0xE0,0,0x10,'J','F','I','F',0,1,1,0,0,1,0,1,0,0,0xFF,0xDB,0,0x84,0 };
+      static const unsigned char head2[] = { 0xFF,0xDA,0,0xC,3,1,0,2,0x11,3,0x11,0,0x3F,0 };
+      const unsigned char head1[] = { 0xFF,0xC0,0,0x11,8,(unsigned char)(height>>8),STBIW_UCHAR(height),(unsigned char)(width>>8),STBIW_UCHAR(width),
+                                      3,1,(unsigned char)(subsample?0x22:0x11),0,2,0x11,1,3,0x11,1,0xFF,0xC4,0x01,0xA2,0 };
+      s->func(s->context, (void*)head0, sizeof(head0));
+      s->func(s->context, (void*)YTable, sizeof(YTable));
+      stbiw__putc(s, 1);
+      s->func(s->context, UVTable, sizeof(UVTable));
+      s->func(s->context, (void*)head1, sizeof(head1));
+      s->func(s->context, (void*)(std_dc_luminance_nrcodes+1), sizeof(std_dc_luminance_nrcodes)-1);
+      s->func(s->context, (void*)std_dc_luminance_values, sizeof(std_dc_luminance_values));
+      stbiw__putc(s, 0x10); // HTYACinfo
+      s->func(s->context, (void*)(std_ac_luminance_nrcodes+1), sizeof(std_ac_luminance_nrcodes)-1);
+      s->func(s->context, (void*)std_ac_luminance_values, sizeof(std_ac_luminance_values));
+      stbiw__putc(s, 1); // HTUDCinfo
+      s->func(s->context, (void*)(std_dc_chrominance_nrcodes+1), sizeof(std_dc_chrominance_nrcodes)-1);
+      s->func(s->context, (void*)std_dc_chrominance_values, sizeof(std_dc_chrominance_values));
+      stbiw__putc(s, 0x11); // HTUACinfo
+      s->func(s->context, (void*)(std_ac_chrominance_nrcodes+1), sizeof(std_ac_chrominance_nrcodes)-1);
+      s->func(s->context, (void*)std_ac_chrominance_values, sizeof(std_ac_chrominance_values));
+      s->func(s->context, (void*)head2, sizeof(head2));
+   }
+
+   // Encode 8x8 macroblocks
+   {
+      static const unsigned short fillBits[] = {0x7F, 7};
+      int DCY=0, DCU=0, DCV=0;
+      int bitBuf=0, bitCnt=0;
+      // comp == 2 is grey+alpha (alpha is ignored)
+      int ofsG = comp > 2 ? 1 : 0, ofsB = comp > 2 ? 2 : 0;
+      const unsigned char *dataR = (const unsigned char *)data;
+      const unsigned char *dataG = dataR + ofsG;
+      const unsigned char *dataB = dataR + ofsB;
+      int x, y, pos;
+      if(subsample) {
+         for(y = 0; y < height; y += 16) {
+            for(x = 0; x < width; x += 16) {
+               float Y[256], U[256], V[256];
+               for(row = y, pos = 0; row < y+16; ++row) {
+                  // row >= height => use last input row
+                  int clamped_row = (row < height) ? row : height - 1;
+                  int base_p = (stbi__flip_vertically_on_write ? (height-1-clamped_row) : clamped_row)*width*comp;
+                  for(col = x; col < x+16; ++col, ++pos) {
+                     // if col >= width => use pixel from last input column
+                     int p = base_p + ((col < width) ? col : (width-1))*comp;
+                     float r = dataR[p], g = dataG[p], b = dataB[p];
+                     Y[pos]= +0.29900f*r + 0.58700f*g + 0.11400f*b - 128;
+                     U[pos]= -0.16874f*r - 0.33126f*g + 0.50000f*b;
+                     V[pos]= +0.50000f*r - 0.41869f*g - 0.08131f*b;
+                  }
+               }
+               DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y+0,   16, fdtbl_Y, DCY, YDC_HT, YAC_HT);
+               DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y+8,   16, fdtbl_Y, DCY, YDC_HT, YAC_HT);
+               DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y+128, 16, fdtbl_Y, DCY, YDC_HT, YAC_HT);
+               DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y+136, 16, fdtbl_Y, DCY, YDC_HT, YAC_HT);
+
+               // subsample U,V
+               {
+                  float subU[64], subV[64];
+                  int yy, xx;
+                  for(yy = 0, pos = 0; yy < 8; ++yy) {
+                     for(xx = 0; xx < 8; ++xx, ++pos) {
+                        int j = yy*32+xx*2;
+                        subU[pos] = (U[j+0] + U[j+1] + U[j+16] + U[j+17]) * 0.25f;
+                        subV[pos] = (V[j+0] + V[j+1] + V[j+16] + V[j+17]) * 0.25f;
+                     }
+                  }
+                  DCU = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, subU, 8, fdtbl_UV, DCU, UVDC_HT, UVAC_HT);
+                  DCV = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, subV, 8, fdtbl_UV, DCV, UVDC_HT, UVAC_HT);
+               }
+            }
+         }
+      } else {
+         for(y = 0; y < height; y += 8) {
+            for(x = 0; x < width; x += 8) {
+               float Y[64], U[64], V[64];
+               for(row = y, pos = 0; row < y+8; ++row) {
+                  // row >= height => use last input row
+                  int clamped_row = (row < height) ? row : height - 1;
+                  int base_p = (stbi__flip_vertically_on_write ? (height-1-clamped_row) : clamped_row)*width*comp;
+                  for(col = x; col < x+8; ++col, ++pos) {
+                     // if col >= width => use pixel from last input column
+                     int p = base_p + ((col < width) ? col : (width-1))*comp;
+                     float r = dataR[p], g = dataG[p], b = dataB[p];
+                     Y[pos]= +0.29900f*r + 0.58700f*g + 0.11400f*b - 128;
+                     U[pos]= -0.16874f*r - 0.33126f*g + 0.50000f*b;
+                     V[pos]= +0.50000f*r - 0.41869f*g - 0.08131f*b;
+                  }
+               }
+
+               DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y, 8, fdtbl_Y,  DCY, YDC_HT, YAC_HT);
+               DCU = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, U, 8, fdtbl_UV, DCU, UVDC_HT, UVAC_HT);
+               DCV = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, V, 8, fdtbl_UV, DCV, UVDC_HT, UVAC_HT);
+            }
+         }
+      }
+
+      // Do the bit alignment of the EOI marker
+      stbiw__jpg_writeBits(s, &bitBuf, &bitCnt, fillBits);
+   }
+
+   // EOI
+   stbiw__putc(s, 0xFF);
+   stbiw__putc(s, 0xD9);
+
+   return 1;
+}
+
+STBIWDEF int stbi_write_jpg_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data, int quality)
+{
+   stbi__write_context s = { 0 };
+   stbi__start_write_callbacks(&s, func, context);
+   return stbi_write_jpg_core(&s, x, y, comp, (void *) data, quality);
+}
+
+
+#ifndef STBI_WRITE_NO_STDIO
+STBIWDEF int stbi_write_jpg(char const *filename, int x, int y, int comp, const void *data, int quality)
+{
+   stbi__write_context s = { 0 };
+   if (stbi__start_write_file(&s,filename)) {
+      int r = stbi_write_jpg_core(&s, x, y, comp, data, quality);
+      stbi__end_write_file(&s);
+      return r;
+   } else
+      return 0;
+}
+#endif
+
+#endif // STB_IMAGE_WRITE_IMPLEMENTATION
+
+/* Revision history
+      1.16  (2021-07-11)
+             make Deflate code emit uncompressed blocks when it would otherwise expand
+             support writing BMPs with alpha channel
+      1.15  (2020-07-13) unknown
+      1.14  (2020-02-02) updated JPEG writer to downsample chroma channels
+      1.13
+      1.12
+      1.11  (2019-08-11)
+
+      1.10  (2019-02-07)
+             support utf8 filenames in Windows; fix warnings and platform ifdefs
+      1.09  (2018-02-11)
+             fix typo in zlib quality API, improve STB_I_W_STATIC in C++
+      1.08  (2018-01-29)
+             add stbi__flip_vertically_on_write, external zlib, zlib quality, choose PNG filter
+      1.07  (2017-07-24)
+             doc fix
+      1.06 (2017-07-23)
+             writing JPEG (using Jon Olick's code)
+      1.05   ???
+      1.04 (2017-03-03)
+             monochrome BMP expansion
+      1.03   ???
+      1.02 (2016-04-02)
+             avoid allocating large structures on the stack
+      1.01 (2016-01-16)
+             STBIW_REALLOC_SIZED: support allocators with no realloc support
+             avoid race-condition in crc initialization
+             minor compile issues
+      1.00 (2015-09-14)
+             installable file IO function
+      0.99 (2015-09-13)
+             warning fixes; TGA rle support
+      0.98 (2015-04-08)
+             added STBIW_MALLOC, STBIW_ASSERT etc
+      0.97 (2015-01-18)
+             fixed HDR asserts, rewrote HDR rle logic
+      0.96 (2015-01-17)
+             add HDR output
+             fix monochrome BMP
+      0.95 (2014-08-17)
+             add monochrome TGA output
+      0.94 (2014-05-31)
+             rename private functions to avoid conflicts with stb_image.h
+      0.93 (2014-05-27)
+             warning fixes
+      0.92 (2010-08-01)
+             casts to unsigned char to fix warnings
+      0.91 (2010-07-17)
+             first public release
+      0.90   first internal release
+*/
+
+/*
+------------------------------------------------------------------------------
+This software is available under 2 licenses -- choose whichever you prefer.
+------------------------------------------------------------------------------
+ALTERNATIVE A - MIT License
+Copyright (c) 2017 Sean Barrett
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+of the Software, and to permit persons to whom the Software is furnished to do
+so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+------------------------------------------------------------------------------
+ALTERNATIVE B - Public Domain (www.unlicense.org)
+This is free and unencumbered software released into the public domain.
+Anyone is free to copy, modify, publish, use, compile, sell, or distribute this
+software, either in source code form or as a compiled binary, for any purpose,
+commercial or non-commercial, and by any means.
+In jurisdictions that recognize copyright laws, the author or authors of this
+software dedicate any and all copyright interest in the software to the public
+domain. We make this dedication for the benefit of the public at large and to
+the detriment of our heirs and successors. We intend this dedication to be an
+overt act of relinquishment in perpetuity of all present and future rights to
+this software under copyright law.
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
+ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
+WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+------------------------------------------------------------------------------
+*/

submodules/simple-knn/ext.cpp

@@ -0,0 +1,17 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#include <torch/extension.h>
+#include "spatial.h"
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+  m.def("distCUDA2", &distCUDA2);
+}

submodules/simple-knn/setup.py

@@ -0,0 +1,35 @@
+#
+# Copyright (C) 2023, Inria
+# GRAPHDECO research group, https://team.inria.fr/graphdeco
+# All rights reserved.
+#
+# This software is free for non-commercial, research and evaluation use 
+# under the terms of the LICENSE.md file.
+#
+# For inquiries contact  george.drettakis@inria.fr
+#
+
+from setuptools import setup
+from torch.utils.cpp_extension import CUDAExtension, BuildExtension
+import os
+
+cxx_compiler_flags = []
+
+if os.name == 'nt':
+    cxx_compiler_flags.append("/wd4624")
+
+setup(
+    name="simple_knn",
+    ext_modules=[
+        CUDAExtension(
+            name="simple_knn._C",
+            sources=[
+            "spatial.cu", 
+            "simple_knn.cu",
+            "ext.cpp"],
+            extra_compile_args={"nvcc": [], "cxx": cxx_compiler_flags})
+        ],
+    cmdclass={
+        'build_ext': BuildExtension
+    }
+)

submodules/simple-knn/simple_knn.cu

@@ -0,0 +1,221 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#define BOX_SIZE 1024
+
+#include "cuda_runtime.h"
+#include "device_launch_parameters.h"
+#include "simple_knn.h"
+#include <cub/cub.cuh>
+#include <cub/device/device_radix_sort.cuh>
+#include <vector>
+#include <cuda_runtime_api.h>
+#include <thrust/device_vector.h>
+#include <thrust/sequence.h>
+#define __CUDACC__
+#include <cooperative_groups.h>
+#include <cooperative_groups/reduce.h>
+
+namespace cg = cooperative_groups;
+
+struct CustomMin
+{
+	__device__ __forceinline__
+		float3 operator()(const float3& a, const float3& b) const {
+		return { min(a.x, b.x), min(a.y, b.y), min(a.z, b.z) };
+	}
+};
+
+struct CustomMax
+{
+	__device__ __forceinline__
+		float3 operator()(const float3& a, const float3& b) const {
+		return { max(a.x, b.x), max(a.y, b.y), max(a.z, b.z) };
+	}
+};
+
+__host__ __device__ uint32_t prepMorton(uint32_t x)
+{
+	x = (x | (x << 16)) & 0x030000FF;
+	x = (x | (x << 8)) & 0x0300F00F;
+	x = (x | (x << 4)) & 0x030C30C3;
+	x = (x | (x << 2)) & 0x09249249;
+	return x;
+}
+
+__host__ __device__ uint32_t coord2Morton(float3 coord, float3 minn, float3 maxx)
+{
+	uint32_t x = prepMorton(((coord.x - minn.x) / (maxx.x - minn.x)) * ((1 << 10) - 1));
+	uint32_t y = prepMorton(((coord.y - minn.y) / (maxx.y - minn.y)) * ((1 << 10) - 1));
+	uint32_t z = prepMorton(((coord.z - minn.z) / (maxx.z - minn.z)) * ((1 << 10) - 1));
+
+	return x | (y << 1) | (z << 2);
+}
+
+__global__ void coord2Morton(int P, const float3* points, float3 minn, float3 maxx, uint32_t* codes)
+{
+	auto idx = cg::this_grid().thread_rank();
+	if (idx >= P)
+		return;
+
+	codes[idx] = coord2Morton(points[idx], minn, maxx);
+}
+
+struct MinMax
+{
+	float3 minn;
+	float3 maxx;
+};
+
+__global__ void boxMinMax(uint32_t P, float3* points, uint32_t* indices, MinMax* boxes)
+{
+	auto idx = cg::this_grid().thread_rank();
+
+	MinMax me;
+	if (idx < P)
+	{
+		me.minn = points[indices[idx]];
+		me.maxx = points[indices[idx]];
+	}
+	else
+	{
+		me.minn = { FLT_MAX, FLT_MAX, FLT_MAX };
+		me.maxx = { -FLT_MAX,-FLT_MAX,-FLT_MAX };
+	}
+
+	__shared__ MinMax redResult[BOX_SIZE];
+
+	for (int off = BOX_SIZE / 2; off >= 1; off /= 2)
+	{
+		if (threadIdx.x < 2 * off)
+			redResult[threadIdx.x] = me;
+		__syncthreads();
+
+		if (threadIdx.x < off)
+		{
+			MinMax other = redResult[threadIdx.x + off];
+			me.minn.x = min(me.minn.x, other.minn.x);
+			me.minn.y = min(me.minn.y, other.minn.y);
+			me.minn.z = min(me.minn.z, other.minn.z);
+			me.maxx.x = max(me.maxx.x, other.maxx.x);
+			me.maxx.y = max(me.maxx.y, other.maxx.y);
+			me.maxx.z = max(me.maxx.z, other.maxx.z);
+		}
+		__syncthreads();
+	}
+
+	if (threadIdx.x == 0)
+		boxes[blockIdx.x] = me;
+}
+
+__device__ __host__ float distBoxPoint(const MinMax& box, const float3& p)
+{
+	float3 diff = { 0, 0, 0 };
+	if (p.x < box.minn.x || p.x > box.maxx.x)
+		diff.x = min(abs(p.x - box.minn.x), abs(p.x - box.maxx.x));
+	if (p.y < box.minn.y || p.y > box.maxx.y)
+		diff.y = min(abs(p.y - box.minn.y), abs(p.y - box.maxx.y));
+	if (p.z < box.minn.z || p.z > box.maxx.z)
+		diff.z = min(abs(p.z - box.minn.z), abs(p.z - box.maxx.z));
+	return diff.x * diff.x + diff.y * diff.y + diff.z * diff.z;
+}
+
+template<int K>
+__device__ void updateKBest(const float3& ref, const float3& point, float* knn)
+{
+	float3 d = { point.x - ref.x, point.y - ref.y, point.z - ref.z };
+	float dist = d.x * d.x + d.y * d.y + d.z * d.z;
+	for (int j = 0; j < K; j++)
+	{
+		if (knn[j] > dist)
+		{
+			float t = knn[j];
+			knn[j] = dist;
+			dist = t;
+		}
+	}
+}
+
+__global__ void boxMeanDist(uint32_t P, float3* points, uint32_t* indices, MinMax* boxes, float* dists)
+{
+	int idx = cg::this_grid().thread_rank();
+	if (idx >= P)
+		return;
+
+	float3 point = points[indices[idx]];
+	float best[3] = { FLT_MAX, FLT_MAX, FLT_MAX };
+
+	for (int i = max(0, idx - 3); i <= min(P - 1, idx + 3); i++)
+	{
+		if (i == idx)
+			continue;
+		updateKBest<3>(point, points[indices[i]], best);
+	}
+
+	float reject = best[2];
+	best[0] = FLT_MAX;
+	best[1] = FLT_MAX;
+	best[2] = FLT_MAX;
+
+	for (int b = 0; b < (P + BOX_SIZE - 1) / BOX_SIZE; b++)
+	{
+		MinMax box = boxes[b];
+		float dist = distBoxPoint(box, point);
+		if (dist > reject || dist > best[2])
+			continue;
+
+		for (int i = b * BOX_SIZE; i < min(P, (b + 1) * BOX_SIZE); i++)
+		{
+			if (i == idx)
+				continue;
+			updateKBest<3>(point, points[indices[i]], best);
+		}
+	}
+	dists[indices[idx]] = (best[0] + best[1] + best[2]) / 3.0f;
+}
+
+void SimpleKNN::knn(int P, float3* points, float* meanDists)
+{
+	float3* result;
+	cudaMalloc(&result, sizeof(float3));
+	size_t temp_storage_bytes;
+
+	float3 init = { 0, 0, 0 }, minn, maxx;
+
+	cub::DeviceReduce::Reduce(nullptr, temp_storage_bytes, points, result, P, CustomMin(), init);
+	thrust::device_vector<char> temp_storage(temp_storage_bytes);
+
+	cub::DeviceReduce::Reduce(temp_storage.data().get(), temp_storage_bytes, points, result, P, CustomMin(), init);
+	cudaMemcpy(&minn, result, sizeof(float3), cudaMemcpyDeviceToHost);
+
+	cub::DeviceReduce::Reduce(temp_storage.data().get(), temp_storage_bytes, points, result, P, CustomMax(), init);
+	cudaMemcpy(&maxx, result, sizeof(float3), cudaMemcpyDeviceToHost);
+
+	thrust::device_vector<uint32_t> morton(P);
+	thrust::device_vector<uint32_t> morton_sorted(P);
+	coord2Morton << <(P + 255) / 256, 256 >> > (P, points, minn, maxx, morton.data().get());
+
+	thrust::device_vector<uint32_t> indices(P);
+	thrust::sequence(indices.begin(), indices.end());
+	thrust::device_vector<uint32_t> indices_sorted(P);
+
+	cub::DeviceRadixSort::SortPairs(nullptr, temp_storage_bytes, morton.data().get(), morton_sorted.data().get(), indices.data().get(), indices_sorted.data().get(), P);
+	temp_storage.resize(temp_storage_bytes);
+
+	cub::DeviceRadixSort::SortPairs(temp_storage.data().get(), temp_storage_bytes, morton.data().get(), morton_sorted.data().get(), indices.data().get(), indices_sorted.data().get(), P);
+
+	uint32_t num_boxes = (P + BOX_SIZE - 1) / BOX_SIZE;
+	thrust::device_vector<MinMax> boxes(num_boxes);
+	boxMinMax << <num_boxes, BOX_SIZE >> > (P, points, indices_sorted.data().get(), boxes.data().get());
+	boxMeanDist << <num_boxes, BOX_SIZE >> > (P, points, indices_sorted.data().get(), boxes.data().get(), meanDists);
+
+	cudaFree(result);
+}

submodules/simple-knn/simple_knn.egg-info/PKG-INFO

@@ -0,0 +1,3 @@
+Metadata-Version: 2.1
+Name: simple-knn
+Version: 0.0.0

submodules/simple-knn/simple_knn.egg-info/SOURCES.txt

@@ -0,0 +1,8 @@
+ext.cpp
+setup.py
+simple_knn.cu
+spatial.cu
+simple_knn.egg-info/PKG-INFO
+simple_knn.egg-info/SOURCES.txt
+simple_knn.egg-info/dependency_links.txt
+simple_knn.egg-info/top_level.txt

submodules/simple-knn/simple_knn.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

submodules/simple-knn/simple_knn.egg-info/top_level.txt

@@ -0,0 +1 @@
+simple_knn

submodules/simple-knn/simple_knn.h

@@ -0,0 +1,21 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#ifndef SIMPLEKNN_H_INCLUDED
+#define SIMPLEKNN_H_INCLUDED
+
+class SimpleKNN
+{
+public:
+	static void knn(int P, float3* points, float* meanDists);
+};
+
+#endif

submodules/simple-knn/spatial.cu

@@ -0,0 +1,26 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#include "spatial.h"
+#include "simple_knn.h"
+
+torch::Tensor
+distCUDA2(const torch::Tensor& points)
+{
+  const int P = points.size(0);
+
+  auto float_opts = points.options().dtype(torch::kFloat32);
+  torch::Tensor means = torch::full({P}, 0.0, float_opts);
+  
+  SimpleKNN::knn(P, (float3*)points.contiguous().data<float>(), means.contiguous().data<float>());
+
+  return means;
+}

submodules/simple-knn/spatial.h

@@ -0,0 +1,14 @@
+/*
+ * Copyright (C) 2023, Inria
+ * GRAPHDECO research group, https://team.inria.fr/graphdeco
+ * All rights reserved.
+ *
+ * This software is free for non-commercial, research and evaluation use 
+ * under the terms of the LICENSE.md file.
+ *
+ * For inquiries contact  george.drettakis@inria.fr
+ */
+
+#include <torch/extension.h>
+
+torch::Tensor distCUDA2(const torch::Tensor& points);