print the current order of elements

Compute the depth-map for the un-rectified image from the given disparity-map of the rectified image by projecting the point-cloud to the image and se

project mesh to the given camera plane

project mesh to the given camera plane

project mesh to the given camera plane using orthographic projection

increase point weights for the points close to the camera

Given an attribute name, QueryAttribute() returns XML_SUCCESS, XML_WRONG_ATTRIBUTE_TYPE if the conversion can't be performed, or XML_NO_ATTR

find the matching "elem" by brute-force (back to front) returns the first element found

Compute a weight for each point in the scene point cloud based on: - proximity to image center - depth from camera - number of views observing the poi

Inverse of the square root Compute a fast 1 / sqrtf(v) approximation

See: colmap/src/base/reconstruction.cc void Reconstruction::ReadCamerasBinary(const std::string& path)

See: colmap/src/base/reconstruction.cc void Reconstruction::ReadImagesBinary(const std::string& path)

See: colmap/src/base/reconstruction.cc void Reconstruction::ReadPoints3DBinary(const std::string& path)

Camera list with one line of data per camera: CAMERA_ID, MODEL, WIDTH, HEIGHT, PARAMS[]

Image list with two lines of data per image: IMAGE_ID, QW, QX, QY, QZ, TX, TY, TZ, CAMERA_ID, NAME POINTS2D[] as (X, Y, POINT3D_ID)

3D point list with one line of data per point: POINT3D_ID, X, Y, Z, R, G, B, ERROR, TRACK[] as (IMAGE_ID, POINT2D_IDX)

Append log messages from the Log system (may be called from any thread)

Sub-pixel disparity-map refinement based on the accumulated-cost volume

Register a new type of log messages (LOGTYPE_SIZE chars)

same as Empty(), plus free all allocated memory