Dockerfile with example cpp to reconstruct 3D points from multiple 2D…

… images

Dockerfile

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+FROM python:3.5
+MAINTAINER Alyssa Quek
+
+# Common libs and for OpenCV
+RUN apt-get update && \
+  apt-get install -y \
+  build-essential \
+  cmake \
+  git \
+  wget \
+  unzip \
+  yasm \
+  vim \
+  ninja-build \
+  pkg-config \
+  libswscale-dev \
+  libtbb2 \
+  libtbb-dev \
+  libjpeg-dev \
+  libpng-dev \
+  libtiff-dev \
+  libjasper-dev \
+  libavformat-dev \
+  libpq-dev \
+  libeigen3-dev
+
+# SFM dependencies: google-glog + gflags, blas + lapack, suitespare, VTK (viz toolkit)
+RUN apt-get install -y \
+  libgoogle-glog-dev \
+  libatlas-base-dev \
+  libsuitesparse-dev \
+  libvtk5-dev \
+  python-vtk \
+  libgtk2.0-dev \
+  libqt4-dev
+
+RUN pip install --upgrade pip && pip install numpy
+
+# Install Ceres Solver
+WORKDIR /
+RUN git clone https://ceres-solver.googlesource.com/ceres-solver \
+  && cd ceres-solver \
+  && mkdir build && cd build \
+  && cmake -G Ninja .. \
+  && ninja -j4 \
+  && ninja install \
+  && ldconfig
+
+ENV PKG_CONFIG_PATH=/usr/local/lib/pkgconfig:/usr/local/share/pkgconfig:/usr/lib/pkgconfig
+# Include eigen into C++ build include
+ENV CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/usr/include/eigen3/:/usr/local/include/opencv:/usr/local/include/opencv2
+ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib
+
+WORKDIR /
+
+# Force HAVE_EIGEN and GFLAGS_FOUND to TRUE as cmake does not seem to set those flags correctly
+RUN cv_version=master \
+  && wget https://github.com/opencv/opencv/archive/"$cv_version".zip -O opencv.zip \
+  && unzip opencv.zip \
+  && wget https://github.com/opencv/opencv_contrib/archive/"$cv_version".zip -O opencv_contrib.zip \
+  && unzip opencv_contrib \
+  && mkdir /opencv-"$cv_version"/cmake_binary \
+  && cd /opencv-"$cv_version"/cmake_binary \
+  && cmake -G Ninja \
+    -DOPENCV_EXTRA_MODULES_PATH=/opencv_contrib-"$cv_version"/modules \
+    -DHAVE_EIGEN=TRUE -DGFLAGS_FOUND=TRUE \
+    -DBUILD_TIFF=ON \
+    -DENABLE_AVX=ON \
+    -DWITH_OPENGL=ON \
+    -DWITH_OPENCL=ON \
+    -DWITH_IPP=ON \
+    -DWITH_TBB=ON \
+    -DWITH_EIGEN=ON \
+    -DWITH_VTK=ON \
+    -DWITH_V4L=ON \
+    -DBUILD_EXAMPLES=ON \
+    -DINSTALL_C_EXAMPLES=ON \
+    -DINSTALL_PYTHON_EXAMPLES=ON \
+    -DBUILD_TESTS=OFF \
+    -DBUILD_PERF_TESTS=OFF \
+    -DCMAKE_BUILD_TYPE=RELEASE \
+    -DCMAKE_INSTALL_PREFIX=$(python3.5 -c "import sys; print(sys.prefix)") \
+    -DPYTHON_EXECUTABLE=$(which python3.5) \
+    -DPYTHON_INCLUDE_DIR=$(python3.5 -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())") \
+    -DPYTHON_PACKAGES_PATH=$(python3.5 -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())") .. \
+  && ninja -j4 install \
+  && rm /opencv.zip \
+  && rm /opencv_contrib.zip
+
+RUN pip install -r requirements.txt
+
+# Define default command
+CMD ["bash"]

README

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+# 3D reconstruction from multiple 2D images
+
+The current structure from motion (SFM) module only runs in Linux.
+As such, I used [docker](https://www.docker.com) on my Mac to reconstruct the 3D points.
+
+## Docker Dev Environment
+```sh
+# Build the docker image
+docker build -t python-opencv .
+# Run the docker container mounting `reconstruction` folder to `/app`
+docker run -it -v <path_to_reconstruction_folder>:/app python-opencv /bin/bash
+```
+
+## Run
+1) Download 2D temple images from <http://vision.middlebury.edu/mview/data>
+2) Save list of images to `images.txt`:
+```sh
+# images.txt will contain lines of filepath
+# /app/temple/temple0302.png
+ls temple/*.png > images.txt
+sed -i -e 's/^/\/app\//' images.txt
+```
+3) In the docker container, compile the cpp file
+```
+g++ example_sfm.cpp  -L/usr/local/lib/  -lopencv_core -lopencv_sfm -lopencv_viz
+```
+4) Run the example with the list of images
+```
+./a.out images.txt 350 240 360
+```
+
+## Test
+```sh
+# Test eigen
+g++ -I /usr/local/Cellar/eigen/3.2.10/include/eigen3/ eigen_test.cpp -o eigen
+./a.out
+
+
+# Test with full includes
+g++ example_sfm.cpp -I /usr/include/eigen3/ -I/usr/local/include/opencv -I/usr/local/include/opencv2 -L /usr/local/share/OpenCV/3rdparty/lib/ -L/usr/local/lib/ -L /usr/include/eigen3/ -lopencv_core -lopencv_imgproc -lopencv_highgui -lopencv_ml -lopencv_optflow -lopencv_sfm -lopencv_viz
+```

example_sfm.cpp

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+#define CERES_FOUND true
+
+#include <opencv2/sfm.hpp>
+#include <opencv2/viz.hpp>
+#include <opencv2/calib3d.hpp>
+#include <opencv2/core.hpp>
+#include <iostream>
+#include <fstream>
+#include <string>
+#include <iomanip>
+using namespace std;
+using namespace cv;
+using namespace cv::sfm;
+
+static void help() {
+  cout
+      << "\n------------------------------------------------------------------------------------\n"
+      << " This program shows the multiview reconstruction capabilities in the \n"
+      << " OpenCV Structure From Motion (SFM) module.\n"
+      << " It reconstruct a scene from a set of 2D images \n"
+      << " Usage:\n"
+      << "        example_sfm_scene_reconstruction <path_to_file> <f> <cx> <cy>\n"
+      << " where: path_to_file is the file absolute path into your system which contains\n"
+      << "        the list of images to use for reconstruction. \n"
+      << "        f  is the focal lenght in pixels. \n"
+      << "        cx is the image principal point x coordinates in pixels. \n"
+      << "        cy is the image principal point y coordinates in pixels. \n"
+      << "------------------------------------------------------------------------------------\n\n"
+      << endl;
+}
+int getdir(const string _filename, vector<string> &files)
+{
+  ifstream myfile(_filename.c_str());
+  if (!myfile.is_open()) {
+    cout << "Unable to read file: " << _filename << endl;
+    exit(0);
+  } else {;
+    size_t found = _filename.find_last_of("/\\");
+    string line_str, path_to_file = _filename.substr(0, found);
+    while ( getline(myfile, line_str) ) {
+      cout << line_str << endl;
+      files.push_back(line_str);
+    }
+  }
+  return 1;
+}
+int main(int argc, char* argv[])
+{
+  // Read input parameters
+  if ( argc != 5 )
+  {
+    help();
+    exit(0);
+  }
+  // Parse the image paths
+  vector<string> images_paths;
+  getdir( argv[1], images_paths );
+  // Build instrinsics
+  float f  = atof(argv[2]),
+        cx = atof(argv[3]), cy = atof(argv[4]);
+  Matx33d K = Matx33d( f, 0, cx,
+                       0, f, cy,
+                       0, 0,  1);
+  bool is_projective = true;
+  vector<Mat> Rs_est, ts_est, points3d_estimated;
+  sfm::reconstruct(images_paths, Rs_est, ts_est, K, points3d_estimated, is_projective);
+
+  // Print output
+  cout << "\n----------------------------\n" << endl;
+  cout << "Reconstruction: " << endl;
+  cout << "============================" << endl;
+  cout << "Estimated 3D points: " << points3d_estimated.size() << endl;
+  cout << "Estimated cameras: " << Rs_est.size() << endl;
+  cout << "Refined intrinsics: " << endl << K << endl << endl;
+  cout << "3D Visualization: " << endl;
+  cout << "============================" << endl;
+  viz::Viz3d window("Coordinate Frame");
+             window.setWindowSize(Size(500,500));
+             window.setWindowPosition(Point(150,150));
+             window.setBackgroundColor(); // black by default
+  // Create the pointcloud
+  cout << "Recovering points  ... ";
+
+  // recover estimated points3d
+  ofstream points_file;
+  cv::MatIterator_<double> mat_it;
+  points_file.open("points.txt");
+  points_file.precision(std::numeric_limits<double>::digits10);
+  for (int i = 0; i < points3d_estimated.size(); ++i) {
+    std::cout << points3d_estimated[i] << std::endl;
+    for(mat_it = points3d_estimated[i].begin<double>(); mat_it != points3d_estimated[i].end<double>(); mat_it++){
+      points_file << *mat_it << " ";
+    }
+    points_file << "\n";
+  }
+  cout << "Done. Points saved to points.txt" << endl;
+  points_file.close();
+
+  return 0;
+}

requirements.txt

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+matplotlib
+scipy
+docopt
+Pillow
+future
+ipython