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Copy pathcolmap.cpp
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Copy pathcolmap.cpp
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170 lines (134 loc) · 5.96 KB
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#include<filesystem>
#include"colmap.hpp"
#include"point_io.hpp"
#include"tensor_math.hpp"
namespacefs= std::filesystem;
usingnamespacetorch::indexing;
namespacecm{
InputData inputDataFromColmap(const std::string &projectRoot){
InputData ret;
fs::path cmRoot(projectRoot);
if (!fs::exists(cmRoot / "cameras.bin") && fs::exists(cmRoot / "sparse" / "0" / "cameras.bin")){
cmRoot = cmRoot / "sparse" / "0";
}
fs::path camerasPath = cmRoot / "cameras.bin";
fs::path imagesPath = cmRoot / "images.bin";
fs::path pointsPath = cmRoot / "points3D.bin";
if (!fs::exists(camerasPath)) throwstd::runtime_error(camerasPath.string() + " does not exist");
if (!fs::exists(imagesPath)) throwstd::runtime_error(imagesPath.string() + " does not exist");
if (!fs::exists(pointsPath)) throwstd::runtime_error(pointsPath.string() + " does not exist");
std::ifstream camf(camerasPath.string(), std::ios::binary);
if (!camf.is_open()) throwstd::runtime_error("Cannot open " + camerasPath.string());
std::ifstream imgf(imagesPath.string(), std::ios::binary);
if (!imgf.is_open()) throwstd::runtime_error("Cannot open " + imagesPath.string());
size_t numCameras = readBinary<uint64_t>(camf);
std::vector<Camera> cameras(numCameras);
std::unordered_map<uint32_t, Camera *> camMap;
for (size_t i = 0; i < numCameras; i++) {
Camera *cam = &cameras[i];
cam->id = readBinary<uint32_t>(camf);
CameraModel model = static_cast<CameraModel>(readBinary<int>(camf)); // model ID
cam->width = readBinary<uint64_t>(camf);
cam->height = readBinary<uint64_t>(camf);
if (model == SimplePinhole){
cam->fx = readBinary<double>(camf);
cam->fy = cam->fx;
cam->cx = readBinary<double>(camf);
cam->cy = readBinary<double>(camf);
}elseif (model == Pinhole){
cam->fx = readBinary<double>(camf);
cam->fy = readBinary<double>(camf);
cam->cx = readBinary<double>(camf);
cam->cy = readBinary<double>(camf);
}elseif (model == SimpleRadial){
cam->fx = readBinary<double>(camf);
cam->fy = cam->fx;
cam->cx = readBinary<double>(camf);
cam->cy = readBinary<double>(camf);
cam->k1 = readBinary<double>(camf);
}elseif (model == OpenCV){
cam->fx = readBinary<double>(camf);
cam->fy = readBinary<double>(camf);
cam->cx = readBinary<double>(camf);
cam->cy = readBinary<double>(camf);
cam->k1 = readBinary<double>(camf);
cam->k2 = readBinary<double>(camf);
cam->p1 = readBinary<double>(camf);
cam->p2 = readBinary<double>(camf);
}elseif (model == FullOpenCV){
cam->fx = readBinary<double>(camf);
cam->fy = readBinary<double>(camf);
cam->cx = readBinary<double>(camf);
cam->cy = readBinary<double>(camf);
cam->k1 = readBinary<double>(camf);
cam->k2 = readBinary<double>(camf);
cam->p1 = readBinary<double>(camf);
cam->p2 = readBinary<double>(camf);
cam->k3 = readBinary<double>(camf);
cam->k4 = readBinary<double>(camf);
cam->k5 = readBinary<double>(camf);
cam->k6 = readBinary<double>(camf);
}else{
throwstd::runtime_error("Unsupported camera model: " + std::to_string(model));
}
camMap[cam->id] = cam;
}
camf.close();
size_t numImages = readBinary<uint64_t>(imgf);
torch::Tensor unorientedPoses = torch::zeros({static_cast<longint>(numImages), 4, 4}, torch::kFloat32);
for (size_t i = 0; i < numImages; i++){
readBinary<uint32_t>(imgf); // imageId
torch::Tensor qVec = torch::tensor({
readBinary<double>(imgf),
readBinary<double>(imgf),
readBinary<double>(imgf),
readBinary<double>(imgf)
}, torch::kFloat32);
torch::Tensor R = quatToRotMat(qVec);
torch::Tensor T = torch::tensor({
{ readBinary<double>(imgf) },
{ readBinary<double>(imgf) },
{ readBinary<double>(imgf) }
}, torch::kFloat32);
torch::Tensor Rinv = R.transpose(0, 1);
torch::Tensor Tinv = torch::matmul(-Rinv, T);
uint32_t camId = readBinary<uint32_t>(imgf);
Camera cam = *camMap[camId];
char ch = '\0';
std::string filePath = "";
while(true){
imgf.read(&ch, 1);
if (ch == '\0') break;
filePath += ch;
}
// TODO: should "images" be an option?
cam.filePath = (fs::path(projectRoot) / "images" / filePath).string();
unorientedPoses[i].index_put_({Slice(None, 3), Slice(None, 3)}, Rinv);
unorientedPoses[i].index_put_({Slice(None, 3), Slice(3, 4)}, Tinv);
unorientedPoses[i][3][3] = 1.0f;
// Convert COLMAP's camera CRS (OpenCV) to OpenGL
unorientedPoses[i].index_put_({Slice(0, 3), Slice(1,3)}, unorientedPoses[i].index({Slice(0, 3), Slice(1,3)}) * -1.0f);
size_t numPoints2D = readBinary<uint64_t>(imgf);
for (size_t j = 0; j < numPoints2D; j++){
readBinary<double>(imgf); // x
readBinary<double>(imgf); // y
readBinary<uint64_t>(imgf); // point3D ID
}
ret.cameras.push_back(cam);
}
imgf.close();
auto r = autoScaleAndCenterPoses(unorientedPoses);
torch::Tensor poses = std::get<0>(r);
ret.translation = std::get<1>(r);
ret.scale = std::get<2>(r);
for (size_t i = 0; i < ret.cameras.size(); i++){
ret.cameras[i].camToWorld = poses[i];
}
PointSet *pSet = readPointSet(pointsPath.string());
torch::Tensor points = pSet->pointsTensor().clone();
ret.points.xyz = (points - ret.translation) * ret.scale;
ret.points.rgb = pSet->colorsTensor().clone();
RELEASE_POINTSET(pSet);
return ret;
}
}