opencv/modules/3d/test/test_ptcloud_utils.cpp
Rostislav Vasilikhin 82038be4cd
Merge pull request #25221 from savuor:rv/bench_3d
OBJ and PLY loaders extention to support texture coordinates and difused colors #25221

### This PR changes
* Texture coordinates support added to `loadMesh()` and `saveMesh()`
* `loadMesh()` changes its behavior: all vertex attribute arrays (vertex coordinates, colors, normals, texture coordinates) now have the same size and same-index corresponce
  - This makes sense for OBJ files where vertex attribute arrays are independent from each other and are randomly accessed when defining faces
  - Looks like this behavior may also happen in some PLY files; however, it is not implemented until we encounter such files in a wild nature
  - At the same time `loadPointCloud()` keeps its behavior and loads vertex attributes as they are given in the file
* PLY loader supports synonyms for the properties: `diffuse_red`, `diffuse_green` and `diffuse_blue` along with `red`, `green` and `blue`
* `std::vector<cv::Vec3i>` supported as an index array type
* Colors are loaded as [0, 1] floats instead of uchars
  - Since colors are usually saved as floats, internal conversion to uchar at loading significantly drops accuracy
  - Performing uchar conversion does not always makes sense and can be performed by a user if they needs it
* PLY loading fixed: wrong offset ruined x coordinate
* Python tests added for `loadPointCloud` and `loadMesh`

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-04 11:04:52 +03:00

111 lines
3.5 KiB
C++

// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
//
// Copyright (C) 2021, Wanli Zhong <zhongwl2018@mail.sustech.edu.cn>
#include "test_ptcloud_utils.hpp"
namespace opencv_test {
void generatePlane(OutputArray plane_pts, const vector<float> &model, float thr, int num,
const vector<float> &limit)
{
if (plane_pts.channels() == 3 && plane_pts.isVector())
{
// std::vector<cv::Point3f>
plane_pts.create(1, num, CV_32FC3);
}
else
{
// cv::Mat
plane_pts.create(num, 3, CV_32F);
}
cv::RNG rng(0);
auto *plane_pts_ptr = (float *) plane_pts.getMat().data;
// Part of the points are generated for the specific model
// The other part of the points are used to increase the thickness of the plane
int std_num = (int) (num / 2);
// Difference of maximum d between two parallel planes
float d_thr = thr * sqrt(model[0] * model[0] + model[1] * model[1] + model[2] * model[2]);
for (int i = 0; i < num; i++)
{
// Let d change then generate thickness
float d = i < std_num ? model[3] : rng.uniform(model[3] - d_thr, model[3] + d_thr);
float x, y, z;
// c is 0 means the plane is vertical
if (model[2] == 0)
{
z = rng.uniform(limit[4], limit[5]);
if (model[0] == 0)
{
x = rng.uniform(limit[0], limit[1]);
y = -d / model[1];
}
else if (model[1] == 0)
{
x = -d / model[0];
y = rng.uniform(limit[2], limit[3]);
}
else
{
x = rng.uniform(limit[0], limit[1]);
y = -(model[0] * x + d) / model[1];
}
}
// c is not 0
else
{
x = rng.uniform(limit[0], limit[1]);
y = rng.uniform(limit[2], limit[3]);
z = -(model[0] * x + model[1] * y + d) / model[2];
}
plane_pts_ptr[3 * i] = x;
plane_pts_ptr[3 * i + 1] = y;
plane_pts_ptr[3 * i + 2] = z;
}
}
void generateSphere(OutputArray sphere_pts, const vector<float> &model, float thr, int num,
const vector<float> &limit)
{
if (sphere_pts.channels() == 3 && sphere_pts.isVector())
{
// std::vector<cv::Point3f>
sphere_pts.create(1, num, CV_32FC3);
}
else
{
// cv::Mat
sphere_pts.create(num, 3, CV_32F);
}
cv::RNG rng(0);
auto *sphere_pts_ptr = (float *) sphere_pts.getMat().data;
// Part of the points are generated for the specific model
// The other part of the points are used to increase the thickness of the sphere
int sphere_num = (int) (num / 1.5);
for (int i = 0; i < num; i++)
{
// Let r change then generate thickness
float r = i < sphere_num ? model[3] : rng.uniform(model[3] - thr, model[3] + thr);
// Generate a random vector and normalize it.
// Note: these vectors are not spread uniformly across the sphere
Vec3f vec(rng.uniform(limit[0], limit[1]), rng.uniform(limit[2], limit[3]),
rng.uniform(limit[4], limit[5]));
float l = sqrt(vec.dot(vec));
// Normalizes it to have a magnitude of r
vec /= l / r;
sphere_pts_ptr[3 * i] = model[0] + vec[0];
sphere_pts_ptr[3 * i + 1] = model[1] + vec[1];
sphere_pts_ptr[3 * i + 2] = model[2] + vec[2];
}
}
} // opencv_test