opencv/modules/3d/samples/odometry_evaluation.cpp
Rostislav Vasilikhin d49958141e
Merge pull request #22925 from savuor:pytsdf_from_scratch
Fixes #22799

Replaces #21559 which was taken as a base

Connected PR in contrib: [#3388@contrib](https://github.com/opencv/opencv_contrib/pull/3388)

### Changes
OK, now this is more Odometry-related PR than Volume-related. Anyway,
* `Volume` class gets wrapped
* The same was done for helper classes like `VolumeSettings`, `OdometryFrame` and `OdometrySettings`
* `OdometryFrame` constructor signature changed to more convenient where depth goes on 1st place, RGB image on 2nd.
This works better for depth-only `Odometry` algorithms.
* `OdometryFrame` is checked for amount of pyramid layers inside `Odometry::compute()`
* `Odometry` was fully wrapped + more docs added
* Added Python tests for `Odometry`, `OdometryFrame` and `Volume`
* Added Python sample for `Volume`
* Minor fixes including better var names

### 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
2022-12-12 09:40:12 +03:00

227 lines
7.2 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
#include <opencv2/3d.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/3d.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/core/utility.hpp>
#include <opencv2/core/quaternion.hpp>
#include <iostream>
#include <fstream>
using namespace std;
using namespace cv;
#define BILATERAL_FILTER 0// if 1 then bilateral filter will be used for the depth
static
void writeResults( const string& filename, const vector<string>& timestamps, const vector<Mat>& Rt )
{
CV_Assert( timestamps.size() == Rt.size() );
ofstream file( filename.c_str() );
if( !file.is_open() )
return;
cout.precision(4);
for( size_t i = 0; i < Rt.size(); i++ )
{
const Mat& Rt_curr = Rt[i];
if( Rt_curr.empty() )
continue;
CV_Assert( Rt_curr.type() == CV_64FC1 );
Quatd rot = Quatd::createFromRotMat(Rt_curr(Rect(0, 0, 3, 3)));
// timestamp tx ty tz qx qy qz qw
file << timestamps[i] << " " << fixed
<< Rt_curr.at<double>(0,3) << " " << Rt_curr.at<double>(1,3) << " " << Rt_curr.at<double>(2,3) << " "
<< rot.x << " " << rot.y << " " << rot.z << " " << rot.w << endl;
}
file.close();
}
static
void setCameraMatrixFreiburg1(float& fx, float& fy, float& cx, float& cy)
{
fx = 517.3f; fy = 516.5f; cx = 318.6f; cy = 255.3f;
}
static
void setCameraMatrixFreiburg2(float& fx, float& fy, float& cx, float& cy)
{
fx = 520.9f; fy = 521.0f; cx = 325.1f; cy = 249.7f;
}
/*
* This sample helps to evaluate odometry on TUM datasets and benchmark http://vision.in.tum.de/data/datasets/rgbd-dataset.
* At this link you can find instructions for evaluation. The sample runs some opencv odometry and saves a camera trajectory
* to file of format that the benchmark requires. Saved file can be used for online evaluation.
*/
int main(int argc, char** argv)
{
if(argc != 4)
{
cout << "Format: file_with_rgb_depth_pairs trajectory_file odometry_name [Rgbd or ICP or RgbdICP or FastICP]" << endl;
return -1;
}
vector<string> timestamps;
vector<Mat> Rts;
const string filename = argv[1];
ifstream file( filename.c_str() );
if( !file.is_open() )
return -1;
char dlmrt1 = '/';
char dlmrt2 = '\\';
size_t pos1 = filename.rfind(dlmrt1);
size_t pos2 = filename.rfind(dlmrt2);
size_t pos = pos1 < pos2 ? pos1 : pos2;
char dlmrt = pos1 < pos2 ? dlmrt1 : dlmrt2;
string dirname = pos == string::npos ? "" : filename.substr(0, pos) + dlmrt;
const int timestampLength = 17;
const int rgbPathLehgth = 17+8;
const int depthPathLehgth = 17+10;
float fx = 525.0f, // default
fy = 525.0f,
cx = 319.5f,
cy = 239.5f;
if(filename.find("freiburg1") != string::npos)
setCameraMatrixFreiburg1(fx, fy, cx, cy);
if(filename.find("freiburg2") != string::npos)
setCameraMatrixFreiburg2(fx, fy, cx, cy);
Mat cameraMatrix = Mat::eye(3,3,CV_32FC1);
{
cameraMatrix.at<float>(0,0) = fx;
cameraMatrix.at<float>(1,1) = fy;
cameraMatrix.at<float>(0,2) = cx;
cameraMatrix.at<float>(1,2) = cy;
}
OdometrySettings ods;
ods.setCameraMatrix(cameraMatrix);
Odometry odometry;
String odname = string(argv[3]);
if (odname == "Rgbd")
odometry = Odometry(OdometryType::RGB, ods, OdometryAlgoType::COMMON);
else if (odname == "ICP")
odometry = Odometry(OdometryType::DEPTH, ods, OdometryAlgoType::COMMON);
else if (odname == "RgbdICP")
odometry = Odometry(OdometryType::RGB_DEPTH, ods, OdometryAlgoType::COMMON);
else if (odname == "FastICP")
odometry = Odometry(OdometryType::DEPTH, ods, OdometryAlgoType::FAST);
else
{
std::cout << "Can not create Odometry algorithm. Check the passed odometry name." << std::endl;
return -1;
}
OdometryFrame frame_prev, frame_curr;
TickMeter gtm;
int count = 0;
for(int i = 0; !file.eof(); i++)
{
string str;
std::getline(file, str);
if(str.empty()) break;
if(str.at(0) == '#') continue; /* comment */
Mat image, depth;
// Read one pair (rgb and depth)
// example: 1305031453.359684 rgb/1305031453.359684.png 1305031453.374112 depth/1305031453.374112.png
#if BILATERAL_FILTER
TickMeter tm_bilateral_filter;
#endif
{
string rgbFilename = str.substr(timestampLength + 1, rgbPathLehgth );
string timestap = str.substr(0, timestampLength);
string depthFilename = str.substr(2*timestampLength + rgbPathLehgth + 3, depthPathLehgth );
image = imread(dirname + rgbFilename);
depth = imread(dirname + depthFilename, -1);
CV_Assert(!image.empty());
CV_Assert(!depth.empty());
CV_Assert(depth.type() == CV_16UC1);
// scale depth
Mat depth_flt;
depth.convertTo(depth_flt, CV_32FC1, 1.f/5000.f);
#if !BILATERAL_FILTER
depth_flt.setTo(std::numeric_limits<float>::quiet_NaN(), depth == 0);
depth = depth_flt;
#else
tm_bilateral_filter.start();
depth = Mat(depth_flt.size(), CV_32FC1, Scalar(0));
const double depth_sigma = 0.03;
const double space_sigma = 4.5; // in pixels
Mat invalidDepthMask = depth_flt == 0.f;
depth_flt.setTo(-5*depth_sigma, invalidDepthMask);
bilateralFilter(depth_flt, depth, -1, depth_sigma, space_sigma);
depth.setTo(std::numeric_limits<float>::quiet_NaN(), invalidDepthMask);
tm_bilateral_filter.stop();
cout << "Time filter " << tm_bilateral_filter.getTimeSec() << endl;
#endif
timestamps.push_back( timestap );
}
{
Mat gray;
cvtColor(image, gray, COLOR_BGR2GRAY);
frame_curr = OdometryFrame(depth, gray);
Mat Rt;
if(!Rts.empty())
{
TickMeter tm;
tm.start();
gtm.start();
odometry.prepareFrames(frame_curr, frame_prev);
bool res = odometry.compute(frame_curr, frame_prev, Rt);
gtm.stop();
tm.stop();
count++;
cout << "Time " << tm.getTimeSec() << endl;
#if BILATERAL_FILTER
cout << "Time ratio " << tm_bilateral_filter.getTimeSec() / tm.getTimeSec() << endl;
#endif
if(!res)
Rt = Mat::eye(4,4,CV_64FC1);
}
if( Rts.empty() )
Rts.push_back(Mat::eye(4,4,CV_64FC1));
else
{
Mat& prevRt = *Rts.rbegin();
cout << "Rt " << Rt << endl;
Rts.push_back( prevRt * Rt );
}
//if (!frame_prev.empty())
// frame_prev.release();
frame_prev = frame_curr;
frame_curr = OdometryFrame();
//std::swap(frame_prev, frame_curr);
}
}
std::cout << "Average time " << gtm.getAvgTimeSec() << std::endl;
writeResults(argv[2], timestamps, Rts);
return 0;
}