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Update for Rerun 0.11 #18

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Nov 28, 2023
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2 changes: 1 addition & 1 deletion CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@ if(NOT DEFINED CMAKE_CXX_STANDARD)
endif()

include(FetchContent)
FetchContent_Declare(rerun_sdk URL https://github.com/rerun-io/rerun/releases/download/0.10.1/rerun_cpp_sdk.zip)
FetchContent_Declare(rerun_sdk URL https://build.rerun.io/commit/d5153cb/rerun_cpp_sdk.zip) # TODO: 2023-11-24. Update to latest commit.
FetchContent_MakeAvailable(rerun_sdk)

find_package(Eigen3 REQUIRED)
Expand Down
41 changes: 0 additions & 41 deletions src/batch_adapters.hpp

This file was deleted.

72 changes: 72 additions & 0 deletions src/collection_adapters.hpp
Original file line number Diff line number Diff line change
@@ -0,0 +1,72 @@
#pragma once

#include <rerun.hpp>

#include <eigen3/Eigen/Core>
#include <opencv2/core.hpp>

// Adapters so we can log eigen vectors as rerun positions:
template <>
struct rerun::CollectionAdapter<rerun::Position3D, std::vector<Eigen::Vector3f>> {
Collection<rerun::Position3D> operator()(const std::vector<Eigen::Vector3f>& container) {
return Collection<rerun::Position3D>::borrow(container.data(), container.size());
}

Collection<rerun::Position3D> operator()(std::vector<Eigen::Vector3f>&& container) {
std::vector<rerun::Position3D> positions(container.size());
memcpy(positions.data(), container.data(), container.size() * sizeof(Eigen::Vector3f));
return Collection<rerun::Position3D>::take_ownership(std::move(positions));
}
};

// Adapters so we can log an eigen matrix as rerun positions:
template <>
struct rerun::CollectionAdapter<rerun::Position3D, Eigen::Matrix3Xf> {
Collection<rerun::Position3D> operator()(const Eigen::Matrix3Xf& matrix) {
// Sanity check that this is binary compatible.
static_assert(
sizeof(rerun::Position3D) ==
sizeof(Eigen::Matrix3Xf::Scalar) * Eigen::Matrix3Xf::RowsAtCompileTime
);
static_assert(alignof(rerun::Position3D) <= alignof(Eigen::Matrix3Xf::Scalar));
return Collection<rerun::Position3D>::borrow(
// Cast to void because otherwise Rerun will try to do above sanity checks with the wrong type (scalar).
reinterpret_cast<const void*>(matrix.data()),
matrix.cols()
);
}

Collection<rerun::Position3D> operator()(Eigen::Matrix3Xf&& matrix) {
std::vector<rerun::Position3D> positions(matrix.cols());
memcpy(positions.data(), matrix.data(), matrix.size() * sizeof(rerun::Position3D));
return Collection<rerun::Position3D>::take_ownership(std::move(positions));
}
};

// Adapters so we can borrow an OpenCV image easily into Rerun images without copying:
template <>
struct rerun::CollectionAdapter<uint8_t, cv::Mat> {
Collection<uint8_t> operator()(const cv::Mat& img) {
return Collection<uint8_t>::borrow(img.data, img.total() * img.channels());
}

Collection<uint8_t> operator()(cv::Mat&& img) {
std::vector<uint8_t> img_vec(img.total() * img.channels());
img_vec.assign(img.data, img.data + img.total() * img.channels());
return Collection<uint8_t>::take_ownership(std::move(img_vec));
}
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};

// Adapter for extracting tensor dimensions from an OpenCV matrix.
// TODO(https://github.com/rerun-io/rerun/pull/4331): remove `datatypes::`
template <>
struct rerun::CollectionAdapter<rerun::datatypes::TensorDimension, cv::Mat> {
Collection<rerun::datatypes::TensorDimension> operator()(const cv::Mat& img) {
// Only specify the const& operator since there is no way of borrowing the dimensions anyways.
return {
static_cast<size_t>(img.rows),
static_cast<size_t>(img.cols),
static_cast<size_t>(img.channels()),
};
}
};
21 changes: 5 additions & 16 deletions src/main.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
#include <opencv2/imgproc.hpp>
#include <rerun.hpp>

#include "batch_adapters.hpp"
#include "collection_adapters.hpp"

std::vector<Eigen::Vector3f> generate_random_points_vector(int num_points) {
std::vector<Eigen::Vector3f> points(num_points);
Expand Down Expand Up @@ -51,8 +51,8 @@ int main() {
rec.log(
"world/camera",
rerun::Transform3D(
rerun::datatypes::Vec3D(camera_position.data()),
rerun::datatypes::Mat3x3(camera_orientation.data())
rerun::Vec3D(camera_position.data()),
rerun::Mat3x3(camera_orientation.data())
)
);

Expand All @@ -65,20 +65,9 @@ int main() {
}

// Log image to Rerun
// TODO(https://github.com/rerun-io/rerun/pull/4331): remove `datatypes::`
cv::cvtColor(img, img, cv::COLOR_BGR2RGB); // Rerun expects RGB format
// NOTE currently we need to construct a vector to log an image, this will change in the future
// see https://github.com/rerun-io/rerun/issues/3794
std::vector<uint8_t> img_vec(img.total() * img.channels());
img_vec.assign(img.data, img.data + img.total() * img.channels());
rec.log(
"image",
rerun::Image(
{static_cast<size_t>(img.rows),
static_cast<size_t>(img.cols),
static_cast<size_t>(img.channels())},
std::move(img_vec)
)
);
rec.log("image", rerun::Image(img, rerun::datatypes::TensorBuffer::u8(img)));
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return 0;
}