8000 Make it possible to build the MVS doc even when CUDA is not installed by sarlinpe · Pull Request #3078 · colmap/colmap · GitHub
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Make it possible to build the MVS doc even when CUDA is not installed #3078

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Merged
merged 3 commits into from
Dec 26, 2024
Merged

Make it possible to build the MVS doc even when CUDA is not installed #3078

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d5acda7
Split PatchMatchOptions into new file
sarlinpe Dec 25, 2024
5262266
Update pycolmap
sarlinpe Dec 25, 2024
ea1590b
Merge branch 'main' into sarlinpe/include-mvs-pydoc
sarlinpe Dec 25, 2024
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1 change: 1 addition & 0 deletions src/colmap/mvs/CMakeLists.txt
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Expand Up @@ -41,6 +41,7 @@ COLMAP_ADD_LIBRARY(
meshing.h meshing.cc
model.h model.cc
normal_map.h normal_map.cc
patch_match_options.h patch_match_options.cc
workspace.h workspace.cc
PUBLIC_LINK_LIBS
colmap_util
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31 changes: 1 addition & 30 deletions src/colmap/mvs/patch_match.cc
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Expand Up @@ -49,38 +49,9 @@ PatchMatch::PatchMatch(const PatchMatchOptions& options, const Problem& problem)

PatchMatch::~PatchMatch() {}

void PatchMatchOptions::Print() const {
PrintHeading2("PatchMatchOptions");
PrintOption(max_image_size);
PrintOption(gpu_index);
PrintOption(depth_min);
PrintOption(depth_max);
PrintOption(window_radius);
PrintOption(window_step);
PrintOption(sigma_spatial);
PrintOption(sigma_color);
PrintOption(num_samples);
PrintOption(ncc_sigma);
PrintOption(min_triangulation_angle);
PrintOption(incident_angle_sigma);
PrintOption(num_iterations);
PrintOption(geom_consistency);
PrintOption(geom_consistency_regularizer);
PrintOption(geom_consistency_max_cost);
PrintOption(filter);
PrintOption(filter_min_ncc);
PrintOption(filter_min_triangulation_angle);
PrintOption(filter_min_num_consistent);
PrintOption(filter_geom_consistency_max_cost);
PrintOption(write_consistency_graph);
PrintOption(allow_missing_files);
}

void PatchMatch::Problem::Print() const {
PrintHeading2("PatchMatch::Problem");

PrintOption(ref_image_idx);

LOG(INFO) << "ref_image_idx: " << ref_image_idx;
LOG(INFO) << "src_image_idxs: ";
if (!src_image_idxs.empty()) {
for (size_t i = 0; i < src_image_idxs.size() - 1; ++i) {
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121 changes: 1 addition & 120 deletions src/colmap/mvs/patch_match.h
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Expand Up @@ -33,6 +33,7 @@
#include "colmap/mvs/image.h"
#include "colmap/mvs/model.h"
#include "colmap/mvs/normal_map.h"
#include "colmap/mvs/patch_match_options.h"
#ifndef __CUDACC__
#include "colmap/util/base_controller.h"
#include "colmap/util/logging.h"
Expand All @@ -46,130 +47,10 @@
namespace colmap {
namespace mvs {

// Maximum possible window radius for the photometric consistency cost. This
// value is equal to THREADS_PER_BLOCK in patch_match_cuda.cu and the limit
// arises from the shared memory implementation.
const static size_t kMaxPatchMatchWindowRadius = 32;

class ConsistencyGraph;
class PatchMatchCuda;
class Workspace;

struct PatchMatchOptions {
// Maximum image size in either dimension.
int max_image_size = -1;

// Index of the GPU used for patch match. For multi-GPU usage,
// you should separate multiple GPU indices by comma, e.g., "0,1,2,3".
std::string gpu_index = "-1";

// Depth range in which to randomly sample depth hypotheses.
double depth_min = -1.0f;
double depth_max = -1.0f;

// Half window size to compute NCC photo-consistency cost.
int window_radius = 5;

// Number of pixels to skip when computing NCC. For a value of 1, every
// pixel is used to compute the NCC. For larger values, only every n-th row
// and column is used and the computation speed thereby increases roughly by
// a factor of window_step^2. Note that not all combinations of window sizes
// and steps produce nice results, especially if the step is greather than 2.
int window_step = 1;

// Parameters for bilaterally weighted NCC.
double sigma_spatial = -1;
double sigma_color = 0.2f;

// Number of random samples to draw in Monte Carlo sampling.
int num_samples = 15;

// Spread of the NCC likelihood function.
double ncc_sigma = 0.6f;

// Minimum triangulation angle in degrees.
double min_triangulation_angle = 1.0f;

// Spread of the incident angle likelihood function.
double incident_angle_sigma = 0.9f;

// Number of coordinate descent iterations. Each iteration consists
// of four sweeps from left to right, top to bottom, and vice versa.
int num_iterations = 5;

// Whether to add a regularized geometric consistency term to the cost
// function. If true, the `depth_maps` and `normal_maps` must not be null.
bool geom_consistency = true;

// The relative weight of the geometric consistency term w.r.t. to
// the photo-consistency term.
double geom_consistency_regularizer = 0.3f;

// Maximum geometric consistency cost in terms of the forward-backward
// reprojection error in pixels.
double geom_consistency_max_cost = 3.0f;

// Whether to enable filtering.
bool filter = true;

// Minimum NCC coefficient for pixel to be photo-consistent.
double filter_min_ncc = 0.1f;

// Minimum triangulation angle to be stable.
double filter_min_triangulation_angle = 3.0f;

// Minimum number of source images have to be consistent
// for pixel not to be filtered.
int filter_min_num_consistent = 2;

// Maximum forward-backward reprojection error for pixel
// to be geometrically consistent.
double filter_geom_consistency_max_cost = 1.0f;

// Cache size in gigabytes for patch match, which keeps the bitmaps, depth
// maps, and normal maps of this number of images in memory. A higher value
// leads to less disk access and faster computation, while a lower value
// leads to reduced memory usage. Note that a single image can consume a lot
// of memory, if the consistency graph is dense.
double cache_size = 32.0;

// Whether to tolerate missing images/maps in the problem setup
bool allow_missing_files = false;

// Whether to write the consistency graph.
bool write_consistency_graph = false;

void Print() const;
bool Check() const {
if (depth_min != -1.0f || depth_max != -1.0f) {
CHECK_OPTION_LE(depth_min, depth_max);
CHECK_OPTION_GE(depth_min, 0.0f);
}
CHECK_OPTION_LE(window_radius,
static_cast<int>(kMaxPatchMatchWindowRadius));
CHECK_OPTION_GT(sigma_color, 0.0f);
CHECK_OPTION_GT(window_radius, 0);
CHECK_OPTION_GT(window_step, 0);
CHECK_OPTION_LE(window_step, 2);
CHECK_OPTION_GT(num_samples, 0);
CHECK_OPTION_GT(ncc_sigma, 0.0f);
CHECK_OPTION_GE(min_triangulation_angle, 0.0f);
CHECK_OPTION_LT(min_triangulation_angle, 180.0f);
CHECK_OPTION_GT(incident_angle_sigma, 0.0f);
CHECK_OPTION_GT(num_iterations, 0);
CHECK_OPTION_GE(geom_consistency_regularizer, 0.0f);
CHECK_OPTION_GE(geom_consistency_max_cost, 0.0f);
CHECK_OPTION_GE(filter_min_ncc, -1.0f);
CHECK_OPTION_LE(filter_min_ncc, 1.0f);
CHECK_OPTION_GE(filter_min_triangulation_angle, 0.0f);
CHECK_OPTION_LE(filter_min_triangulation_angle, 180.0f);
CHECK_OPTION_GE(filter_min_num_consistent, 0);
CHECK_OPTION_GE(filter_geom_consistency_max_cost, 0.0f);
CHECK_OPTION_GT(cache_size, 0);
return true;
}
};

// This is a wrapper class around the actual PatchMatchCuda implementation. This
// class is necessary to hide Cuda code from any boost or Eigen code, since
// NVCC/MSVC cannot compile complex C++ code.
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101 changes: 101 additions & 0 deletions src/colmap/mvs/patch_match_options.cc
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@@ -0,0 +1,101 @@
// Copyright (c) 2023, ETH Zurich and UNC Chapel Hill.
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of
// its contributors may be used to endorse or promote products derived
// from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS 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 IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.

#include "colmap/mvs/patch_match_options.h"

#include "colmap/util/logging.h"
#include "colmap/util/misc.h"

namespace colmap {
namespace mvs {

// Maximum possible window radius for the photometric consistency cost. This
// value is equal to THREADS_PER_BLOCK in patch_match_cuda.cu and the limit
// arises from the shared memory implementation.
const static size_t kMaxPatchMatchWindowRadius = 32;

#define PrintOption(option) LOG(INFO) << #option ": " << option

void PatchMatchOptions::Print() const {
PrintHeading2("PatchMatchOptions");
PrintOption(max_image_size);
PrintOption(gpu_index);
PrintOption(depth_min);
PrintOption(depth_max);
PrintOption(window_radius);
PrintOption(window_step);
PrintOption(sigma_spatial);
PrintOption(sigma_color);
PrintOption(num_samples);
PrintOption(ncc_sigma);
PrintOption(min_triangulation_angle);
PrintOption(incident_angle_sigma);
PrintOption(num_iterations);
PrintOption(geom_consistency);
PrintOption(geom_consistency_regularizer);
PrintOption(geom_consistency_max_cost);
PrintOption(filter);
PrintOption(filter_min_ncc);
PrintOption(filter_min_triangulation_angle);
PrintOption(filter_min_num_consistent);
PrintOption(filter_geom_consistency_max_cost);
PrintOption(write_consistency_graph);
PrintOption(allow_missing_files);
}

bool PatchMatchOptions::Check() const {
if (depth_min != -1.0f || depth_max != -1.0f) {
CHECK_OPTION_LE(depth_min, depth_max);
CHECK_OPTION_GE(depth_min, 0.0f);
}
CHECK_OPTION_LE(window_radius, static_cast<int>(kMaxPatchMatchWindowRadius));
CHECK_OPTION_GT(sigma_color, 0.0f);
CHECK_OPTION_GT(window_radius, 0);
CHECK_OPTION_GT(window_step, 0);
CHECK_OPTION_LE(window_step, 2);
CHECK_OPTION_GT(num_samples, 0);
CHECK_OPTION_GT(ncc_sigma, 0.0f);
CHECK_OPTION_GE(min_triangulation_angle, 0.0f);
CHECK_OPTION_LT(min_triangulation_angle, 180.0f);
CHECK_OPTION_GT(incident_angle_sigma, 0.0f);
CHECK_OPTION_GT(num_iterations, 0);
CHECK_OPTION_GE(geom_consistency_regularizer, 0.0f);
CHECK_OPTION_GE(geom_consistency_max_cost, 0.0f);
CHECK_OPTION_GE(filter_min_ncc, -1.0f);
CHECK_OPTION_LE(filter_min_ncc, 1.0f);
CHECK_OPTION_GE(filter_min_triangulation_angle, 0.0f);
CHECK_OPTION_LE(filter_min_triangulation_angle, 180.0f);
CHECK_OPTION_GE(filter_min_num_consistent, 0);
CHECK_OPTION_GE(filter_geom_consistency_max_cost, 0.0f);
CHECK_OPTION_GT(cache_size, 0);
return true;
}

} // namespace mvs
} // namespace colmap
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