Fix some of warnings...

camera_models/CMakeLists.txt

@@ -1,4 +1,4 @@
-cmake_minimum_required(VERSION 2.8.3)
+cmake_minimum_required(VERSION 3.0.0)
 project(camera_models)
 
 set(CMAKE_BUILD_TYPE "Release")

d2common/include/d2common/d2frontend_types.h

@@ -217,7 +217,7 @@ struct VisualImageDesc {
                 img_desc.landmark_descriptor_int8.resize(landmark_descriptor.size());
                 img_desc.landmark_descriptor_size = 0;
                 auto max = desc0.cwiseAbs().maxCoeff();
-                for (int i = 0; i < landmark_descriptor.size(); i++) {
+                for (unsigned int i = 0; i < landmark_descriptor.size(); i++) {
                     img_desc.landmark_descriptor_int8[i] = (int8_t)(desc0[i] / max * 127);
                 }
                 img_desc.landmark_scores_size = 0;
@@ -248,7 +248,7 @@ struct VisualImageDesc {
                 img_desc.header.image_desc_int8.resize(image_desc.size());
                 img_desc.header.image_desc_size = 0;
                 double max = Eigen::Map<const VectorXf>(image_desc.data(), image_desc.size()).cwiseAbs().maxCoeff();
-                for (int i = 0; i < image_desc.size(); i++) {
+                for (unsigned int i = 0; i < image_desc.size(); i++) {
                     img_desc.header.image_desc_int8[i] = (int8_t)(image_desc[i] / max * 127);
                 }
             } else {
@@ -304,7 +304,7 @@ struct VisualImageDesc {
         if (desc.landmark_descriptor_int8.size() > 0) {
             landmark_descriptor.resize(desc.landmark_descriptor_int8.size());
             Eigen::Map<VectorXf> desc0(landmark_descriptor.data(), landmark_descriptor.size());
-            for (int i = 0; i < landmark_descriptor.size(); i++) {
+            for (unsigned int i = 0; i < landmark_descriptor.size(); i++) {
                 desc0(i) = desc.landmark_descriptor_int8[i] / 127.0;
             }
             //Per feature normalize the landmark desc
@@ -317,7 +317,7 @@ struct VisualImageDesc {
         if (desc.header.image_desc_size_int8 > 0) {
             image_desc.resize(desc.header.image_desc_size_int8);
             Eigen::Map<VectorXf> gdesc(image_desc.data(), image_desc.size());
-            for (int i = 0; i < image_desc.size(); i++) {
+            for (unsigned int i = 0; i < image_desc.size(); i++) {
                 gdesc(i) = desc.header.image_desc_int8[i] / 127.0;
             }
             gdesc.normalize();

d2common/include/d2common/d2landmarks.h

@@ -5,6 +5,7 @@
 #include <opencv2/opencv.hpp>
 #include "d2basetypes.h"
 #include <swarm_msgs/swarm_lcm_converter.hpp>
+#include <spdlog/spdlog.h>
 
 namespace D2Common {
 enum LandmarkFlag {
@@ -268,7 +269,7 @@ struct LandmarkPerId {
                 return it;
             }
         }
-        printf("LandmarkPerId::at: Error, cannot find frame_id %d\n", frame_id);
+        spdlog::warn("LandmarkPerId::at Warn, cannot find frame_id {}", frame_id);
         return LandmarkPerFrame();
     }
 

d2common/include/d2common/fisheye_undistort.h

@@ -129,7 +129,7 @@ class FisheyeUndist {
             auto _photometics_gpu = undist_all_cuda(photomertic, true);
             photometics = _photometics;
             photometics_gpu = _photometics_gpu;
-            for (int i = 0; i < _photometics.size(); i++) {
+            for (unsigned int i = 0; i < _photometics.size(); i++) {
                 cv::Mat bgr;
                 cv::cvtColor(_photometics[i], bgr, cv::COLOR_GRAY2BGR);
                 photometics_bgr.push_back(bgr);

d2common/include/d2common/integration_base.h

@@ -88,7 +88,7 @@ class IntegrationBase
         linearized_bg = _linearized_bg;
         jacobian.setIdentity();
         covariance.setZero();
-        for (int i = 0; i < static_cast<int>(dt_buf.size()); i++)
+        for (unsigned int i = 0; i < dt_buf.size(); i++)
             propagate(dt_buf[i], acc_buf[i], gyr_buf[i]);
     }
 

d2common/src/d2vinsframe.cpp

@@ -99,7 +99,7 @@ swarm_msgs::VIOFrame VINSFrame::toROS(const std::vector<Swarm::Pose>& exts) {
   msg.is_keyframe = is_keyframe;
   msg.reference_frame_id = reference_frame_id;
   msg.odom = odom.toRos();
-  for (int i = 0; i < exts.size(); i++) {
+  for (unsigned int i = 0; i < exts.size(); i++) {
     msg.extrinsics.emplace_back(exts[i].toROS());
   }
   return msg;

d2common/src/solver/BaseParamResInfo.cpp

@@ -61,7 +61,7 @@ void ResidualInfo::Evaluate(const std::vector<ParamInfo> &param_infos,
   std::vector<int> blk_sizes = cost_function->parameter_block_sizes();
   std::vector<double *> raw_jacobians(blk_sizes.size());
   jacobians.resize(blk_sizes.size());
-  for (int i = 0; i < static_cast<int>(blk_sizes.size()); i++) {
+  for (unsigned int i = 0; i < blk_sizes.size(); i++) {
     jacobians[i].resize(cost_function->num_residuals(), blk_sizes[i]);
     jacobians[i].setZero();
     raw_jacobians[i] = jacobians[i].data();
@@ -83,7 +83,7 @@ void ResidualInfo::Evaluate(const std::vector<ParamInfo> &param_infos,
       residual_scaling_ = sqrt_rho1_ / (1 - alpha);
       alpha_sq_norm_ = alpha / sq_norm;
     }
-    for (int i = 0; i < static_cast<int>(params.size()); i++) {
+    for (unsigned int i = 0; i < params.size(); i++) {
       jacobians[i] = sqrt_rho1_ * (jacobians[i] -
                                    alpha_sq_norm_ * residuals *
                                        (residuals.transpose() * jacobians[i]));

d2frontend/CMakeLists.txt

@@ -1,4 +1,4 @@
-cmake_minimum_required(VERSION 2.8.3)
+cmake_minimum_required(VERSION 3.0.0)
 project(d2frontend)
 
 set(CMAKE_CXX_STANDARD 17)

d2frontend/include/d2frontend/utils.h

@@ -36,7 +36,7 @@ Eigen::VectorXf load_csv_vec_eigen(std::string csv);
 template <typename T, typename B>
 inline void reduceVector(std::vector<T> &v, std::vector<B> status) {
     int j = 0;
-    for (int i = 0; i < int(v.size()); i++)
+    for (unsigned int i = 0; i < v.size(); i++)
         if (status[i])
             v[j++] = v[i];
     v.resize(j);

d2frontend/src/CNN/superpoint.cpp

@@ -174,7 +174,7 @@ bool SuperPoint::infer(const cv::Mat & input, std::vector<cv::Point2f> & keypoin
     }
     // [n_keypoints_num,n]
     for (auto &descriptor : raw_descriptors) {
-        for (int i = 0; i < descriptor.size(); ++i) {
+        for (unsigned int i = 0; i < descriptor.size(); ++i) {
             descriptors.push_back(descriptor[i]);
         }
     }
@@ -201,7 +201,7 @@ bool SuperPoint::processInput(const tensorrt_buffer::BufferManager &buffers, con
 void SuperPoint::findHighScoreIndex(std::vector<float> &scores, std::vector<Eigen::Vector2f> &keypoints,
                                     int h, int w, float threshold) {
     std::vector<float> new_scores;
-    for (int i = 0; i < scores.size(); ++i) {
+    for (unsigned int i = 0; i < scores.size(); ++i) {
         if (scores[i] > threshold) {
             Eigen::Vector2f location = {i % w, int(i / w)}; //u,v
             keypoints.emplace_back(location);
@@ -217,7 +217,7 @@ void SuperPoint::removeBorders( std::vector<Eigen::Vector2f> &keypoints, std::ve
                                 int width) {
     std::vector<Eigen::Vector2f> keypoints_selected;
     std::vector<float> scores_selected;
-    for (int i = 0; i < keypoints.size(); ++i) {
+    for (unsigned int i = 0; i < keypoints.size(); ++i) {
         bool flag_h = (keypoints[i][1] >= border) && (keypoints[i][1] < (height - border)); //v 
         bool flag_w = (keypoints[i][0] >= border) && (keypoints[i][0] < (width - border)); //u
         if (flag_h && flag_w) {
@@ -440,14 +440,14 @@ bool SuperPoint::deserializeEngine(){
 //     Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
 //         _desc_new = (_desc.rowwise() - pca_mean) * pca_comp_T;
 //     // Perform row wise normalization
-//     for (int i = 0; i < _desc_new.rows(); i++) {
+//     for (unsigned int i = 0; i < _desc_new.rows(); i++) {
 //       _desc_new.row(i) /= _desc_new.row(i).norm();
 //     }
 //     local_descriptors = std::vector<float>(
 //         _desc_new.data(),
 //         _desc_new.data() + _desc_new.cols() * _desc_new.rows());
 //   } else {
-//     for (int i = 0; i < _desc.rows(); i++) {
+//     for (unsigned int i = 0; i < _desc.rows(); i++) {
 //       _desc.row(i) /= _desc.row(i).norm();
 //     }
 //     local_descriptors = std::vector<float>(

d2frontend/src/CNN/superpoint_common.cpp

@@ -18,7 +18,7 @@ void getKeyPoints(const cv::Mat& prob, float threshold, int nms_dist,
   std::vector<cv::Point> kps;
   cv::findNonZero(mask, kps);
   std::vector<cv::Point2f> keypoints_no_nms;
-  for (int i = 0; i < kps.size(); i++) {
+  for (unsigned int i = 0; i < kps.size(); i++) {
     keypoints_no_nms.push_back(cv::Point2f(kps[i].x, kps[i].y));
   }
 
@@ -76,14 +76,14 @@ void computeDescriptors(const torch::Tensor& mProb, const torch::Tensor& mDesc,
     Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
         _desc_new = (_desc.rowwise() - pca_mean) * pca_comp_T;
     // Perform row wise normalization
-    for (int i = 0; i < _desc_new.rows(); i++) {
+    for (unsigned int i = 0; i < _desc_new.rows(); i++) {
       _desc_new.row(i) /= _desc_new.row(i).norm();
     }
     local_descriptors = std::vector<float>(
         _desc_new.data(),
         _desc_new.data() + _desc_new.cols() * _desc_new.rows());
   } else {
-    for (int i = 0; i < _desc.rows(); i++) {
+    for (unsigned int i = 0; i < _desc.rows(); i++) {
       _desc.row(i) /= _desc.row(i).norm();
     }
     local_descriptors = std::vector<float>(
@@ -126,7 +126,7 @@ void NMS2(std::vector<cv::Point2f> det, cv::Mat conf,
     confidence.at<float>(vv, uu) = conf.at<float>(i, 0);
   }
 
-  for (int i = 0; i < pts_raw.size(); i++) {
+  for (unsigned int i = 0; i < pts_raw.size(); i++) {
     int uu = (int)pts_raw[i].x;
     int vv = (int)pts_raw[i].y;
 

d2frontend/src/d2featuretracker.cpp

@@ -501,7 +501,7 @@ TrackReport D2FeatureTracker::trackLK(VisualImageDesc &frame) {
                                           TrackLRType::WHOLE_IMG_MATCH);
         pyr_has_built = true;
         cur_lk_info.lk_pts_3d_norm.resize(cur_lk_info.lk_pts.size());
-        for (int i = 0; i < cur_lk_info.lk_pts.size(); i++) {
+        for (unsigned int i = 0; i < cur_lk_info.lk_pts.size(); i++) {
           auto ret =
               createLKLandmark(frame, cur_lk_info.lk_pts[i],
                                cur_lk_info.lk_ids[i], cur_lk_info.lk_types[i]);
@@ -723,7 +723,7 @@ TrackReport D2FeatureTracker::trackLK(const VisualImageDesc &left_frame,
       keyframe_lk_infos.at(left_frame.frame_id).at(left_frame.camera_index);
   // Add the SP points to the LK points if use_lk_for_left_right_track is true
   if (use_lk_for_left_right_track && !_config.sp_track_use_lk) {
-    for (int i = 0; i < left_frame.landmarkNum(); i++) {
+    for (unsigned int i = 0; i < left_frame.landmarkNum(); i++) {
       if (left_frame.landmarks[i].landmark_id >= 0 &&
           left_frame.landmarks[i].type == LandmarkType::SuperPointLandmark) {
         left_lk_info.lk_pts.emplace_back(left_frame.landmarks[i].pt2d);
@@ -745,7 +745,7 @@ TrackReport D2FeatureTracker::trackLK(const VisualImageDesc &left_frame,
   if (!left_lk_info.lk_ids.empty()) {
     auto cur_lk_info =
         opticalflowTrackPyr(right_frame.raw_image, left_lk_info, type);
-    for (int i = 0; i < cur_lk_info.lk_pts.size(); i++) {
+    for (unsigned int i = 0; i < cur_lk_info.lk_pts.size(); i++) {
       auto ret =
           createLKLandmark(right_frame, cur_lk_info.lk_pts[i],
                            cur_lk_info.lk_ids[i], cur_lk_info.lk_types[i]);
@@ -952,7 +952,7 @@ cv::Mat D2FeatureTracker::drawToImage(const VisualImageDesc &frame,
     // Draw predictions here
     auto &predictions = landmark_predictions_viz.at(frame.camera_id);
     auto &prev = landmark_predictions_matched_viz.at(frame.camera_id);
-    for (int i = 0; i < predictions.size(); i++) {
+    for (unsigned int i = 0; i < predictions.size(); i++) {
       cv::circle(img, predictions[i], 3, cv::Scalar(0, 255, 0), 2);
       cv::line(img, prev[i], predictions[i], cv::Scalar(0, 0, 255), 1, 8, 0);
       // if (cv::norm(prev[i] - predictions[i]) > 20) {
@@ -1078,7 +1078,7 @@ std::pair<std::vector<float>, std::vector<cv::Point2f>> getFeatureHalfImg(
   float move_cols =
       params->width_undistort * 90.0 /
       params->undistort_fov;  // slightly lower than 0.5 cols when fov=200
-  for (int i = 0; i < pts.size(); i++) {
+  for (unsigned int i = 0; i < pts.size(); i++) {
     if (require_left && pts[i].x < params->width_undistort - move_cols ||
         !require_left && pts[i].x >= move_cols) {
       tmp_to_idx[c] = i;
@@ -1183,7 +1183,7 @@ bool D2FeatureTracker::matchLocalFeatures(
               params->width_undistort * 90.0 /
               params
                   ->undistort_fov;  // slightly lower than 0.5 cols when fov=200
-          for (int i = 0; i < features_a.second.size(); i++) {
+          for (unsigned int i = 0; i < features_a.second.size(); i++) {
             features_a.second[i].x +=
                 param.type == LEFT_RIGHT_IMG_MATCH ? move_cols : -move_cols;
           }
@@ -1261,10 +1261,10 @@ bool D2FeatureTracker::matchLocalFeatures(
     char name[100];
     std::vector<cv::KeyPoint> kps_a, kps_b;
     // Kps from points
-    for (int i = 0; i < pts_a.size(); i++) {
+    for (unsigned int i = 0; i < pts_a.size(); i++) {
       kps_a.push_back(cv::KeyPoint(pts_a[i].x, pts_a[i].y, 1));
     }
-    for (int i = 0; i < pts_b.size(); i++) {
+    for (unsigned int i = 0; i < pts_b.size(); i++) {
       kps_b.push_back(cv::KeyPoint(pts_b[i].x, pts_b[i].y, 1));
     }
     cv::Mat show;
@@ -1283,7 +1283,7 @@ bool D2FeatureTracker::matchLocalFeatures(
       cv::Mat show_check;
       cv::hconcat(img_desc_a.raw_image, image_b, show_check);
       cv::cvtColor(show_check, show_check, cv::COLOR_GRAY2BGR);
-      for (int i = 0; i < matched_pts_a.size(); i++) {
+      for (unsigned int i = 0; i < matched_pts_a.size(); i++) {
         // random color
         cv::Scalar color(rand() & 255, rand() & 255, rand() & 255);
         cv::line(show_check, matched_pts_a[i],
@@ -1320,7 +1320,7 @@ D2FeatureTracker::predictLandmarksWithExtrinsic(
     const Swarm::Pose &cam_pose_b) const {
   std::map<LandmarkIdType, cv::Point2f> pts_a_pred_on_b;
   auto cam = cams.at(camera_index);
-  for (int i = 0; i < pts_3d_norm.size(); i++) {
+  for (unsigned int i = 0; i < pts_3d_norm.size(); i++) {
     Vector3d landmark_pos_cam =
         pts_3d_norm[i] * _config.landmark_distance_assumption;
     Vector3d pt3d = cam_pose_a * landmark_pos_cam;
@@ -1338,7 +1338,7 @@ std::vector<cv::Point2f> D2FeatureTracker::predictLandmarks(
   std::vector<cv::Point2f> pts_a_pred_on_b;
   assert(img_desc_a.drone_id == params->self_id);
   auto cam = cams.at(img_desc_a.camera_index);
-  for (int i = 0; i < img_desc_a.spLandmarkNum(); i++) {
+  for (unsigned int i = 0; i < img_desc_a.spLandmarkNum(); i++) {
     auto landmark_id = img_desc_a.landmarks[i].landmark_id;
     // Query 3d landmark position
     bool find_position = false;

d2frontend/src/loop_cam.cpp

@@ -117,7 +117,7 @@ double triangulatePoint(Eigen::Quaterniond q0, Eigen::Vector3d t0,
 template <typename T>
 void reduceVector(std::vector<T> &v, std::vector<uchar> status) {
   int j = 0;
-  for (int i = 0; i < int(v.size()); i++)
+  for (unsigned int i = 0; i < v.size(); i++)
     if (status[i]) v[j++] = v[i];
   v.resize(j);
 }

d2frontend/src/loop_detector.cpp

@@ -747,7 +747,7 @@ void LoopDetector::drawMatched(
   }
   std::set<int> inlier_set(inliers.begin(), inliers.end());
 
-  for (int i = 0; i < index2dirindex_a.size(); i++) {
+  for (unsigned int i = 0; i < index2dirindex_a.size(); i++) {
     int old_pt_id = index2dirindex_b[i].second;
     int old_dir_id = index2dirindex_b[i].first;
 

d2frontend/src/loop_utils.cpp

@@ -362,7 +362,7 @@ std::vector<cv::Point2f> opticalflowTrack(const cv::Mat &cur_img,
       status[i] = 0;
   }
 
-  for (int i = 0; i < int(cur_pts.size()); i++) {
+  for (unsigned int i = 0; i < cur_pts.size(); i++) {
     if (status[i] && !inBorder(cur_pts[i], cur_img.size())) {
       status[i] = 0;
     }
@@ -468,7 +468,7 @@ LKImageInfoGPU opticalflowTrackPyr(const cv::Mat &cur_img,
       status[i] = 0;
   }
 
-  for (int i = 0; i < int(cur_pts.size()); i++) {
+  for (unsigned int i = 0; i < cur_pts.size(); i++) {
     if (status[i] && !inBorder(cur_pts[i], cur_img.size())) {
       status[i] = 0;
     }
@@ -580,7 +580,7 @@ std::vector<cv::Point2f> detectFastByRegion(cv::InputArray _img,
               return a.response > b.response;
             });
   // Return the top features
-  for (int i = 0; i < total_kpts.size(); i++) {
+  for (unsigned int i = 0; i < total_kpts.size(); i++) {
     ret.push_back(total_kpts[i].pt);
     if (ret.size() >= features) {
       break;
@@ -632,7 +632,7 @@ int computeRelativePosePnP(const std::vector<Vector3d> lm_positions_a,
   int iteratives = 100;
   Point3fVector pts3d;
   Point2fVector pts2d;
-  for (int i = 0; i < lm_positions_a.size(); i++) {
+  for (unsigned int i = 0; i < lm_positions_a.size(); i++) {
     auto z = lm_3d_norm_b[i].z();
     if (z > 1e-1) {
       pts3d.push_back(cv::Point3f(lm_positions_a[i].x(), lm_positions_a[i].y(),
@@ -676,12 +676,12 @@ Swarm::Pose computePosePnPnonCentral(
   opengv::points_t points;
   opengv::rotations_t camRotations;
   opengv::translations_t camOffsets;
-  for (int i = 0; i < lm_positions_a.size(); i++) {
+  for (unsigned int i = 0; i < lm_positions_a.size(); i++) {
     bearings.push_back(lm_3d_norm_b[i]);
     camCorrespondences.push_back(camera_indices[i]);
     points.push_back(lm_positions_a[i]);
   }
-  for (int i = 0; i < cam_extrinsics.size(); i++) {
+  for (unsigned int i = 0; i < cam_extrinsics.size(); i++) {
     camRotations.push_back(cam_extrinsics[i].R());
     camOffsets.push_back(cam_extrinsics[i].pos());
   }
@@ -714,7 +714,7 @@ Swarm::Pose computePosePnPnonCentral(
   bearings.clear();
   camCorrespondences.clear();
   points.clear();
-  for (int i = 0; i < lm_positions_a.size(); i++) {
+  for (unsigned int i = 0; i < lm_positions_a.size(); i++) {
     if (inlier_set.find(i) == inlier_set.end()) {
       continue;
     }

d2pgo/src/d2pgo.cpp

@@ -470,7 +470,7 @@ void D2PGO::setupLoopFactors(SolverWrapper* solver,
 void D2PGO::setupEgoMotionFactors(SolverWrapper* solver, int drone_id) {
   auto frames = state.getFrames(drone_id);
   auto traj = state.getEgomotionTraj(drone_id);
-  for (int i = 0; i < frames.size() - 1; i++) {
+  for (unsigned int i = 0; i < frames.size() - 1; i++) {
     auto frame_a = frames[i];
     auto frame_b = frames[i + 1];
     Swarm::Pose rel_pose;

d2pgo/src/rot_init/rotation_initialization_base.hpp

@@ -11,7 +11,7 @@ using D2Common::Utility::TicToc;
 
 template <typename Derived, typename T>
 inline void fillInTripet(int i0, int j0, const MatrixBase<Derived> & M, std::vector<Eigen::Triplet<T>> & triplets) {
-    for (int i = 0; i < M.rows(); i ++) { //Row, col of relative rotation R
+    for (unsigned int i = 0; i < M.rows(); i ++) { //Row, col of relative rotation R
         for (int j = 0; j < M.cols(); j ++) {
             triplets.emplace_back(Eigen::Triplet<T>(i0 + i, j0 + j, M(i, j)));
         }