Supported File Formats

the api allows uploading different file formats of images and point clouds in this section we describe the supported formats for each type images we currently support the following image formats png , jpg , jpeg , webp and avif point clouds kognic uses a potree format internally to represent and present point clouds, this means that uploaded point cloud data needs to be converted into this format before it can be used as scene in the system we currently support automatic conversion of the following formats pcd , csv and las the converter does not however exhaustively support all possible versions of these formats, see below for details of each format internally we have a max precision of points coordinates at 1e 6 so 0 0000012 and 0 0000013 is considered the same point to us a timestamp field must always be present in point clouds, both in single frame and sequence scenes, but the values are irrelevant motion compensation docid\ rhbsetwlntflfo6fmd 1e an intensity field may be provided in point clouds and will be preserved during conversion if omitted, the intensity for all points will be zero a color field may be provided in the point clouds and will be preserved during conversion if ommited no color data will be used other auxiliary data that is not used in the platform is currently discarded in the conversion to potree column names must be exact the column names must be provided as documented below if they are not, the conversion will fail in the case of timestamps, default values of 0 will be used instead pcd the currently supported format includes the following header version 7 fields x y z intensity timestamp rgb size 4 4 4 4 8 4 type f f f u u f count 1 1 1 1 1 1 width \<w> height \<h> viewpoint 0 0 0 1 0 0 0 0 points \<n> data ascii apart from ascii as data type, we also support binary and binary compressed note that we currently don't support organized point clouds in the binary compressed case, i e when height is not equal to 1 csv we currently only support the following exact header and using , as separation character (where intensity is uint8, ts gps is an uint64 and x , y , z are all float32) ts gps,x,y,z,intensity,rgb,red,green,blue the rgb fields are optional and can either be specified with just the rgb column or with one column per color if only one of the three columns is set or rgb in combination with the color columns the processing will fail the rgb color is expressed as hex color and the red, green, blue is 255 ints all other formats will fail las we currently support version 1 2 and point format id 3, as defined in the las 1 2 specification https //www asprs org/a/society/committees/standards/asprs las format v12 pdf all other formats will cause the conversion to fail imu data when specifying imu data by file and not by python model we expect the following json \[ { "postion" { "x" 0 0, "y" 0 0, "z" 0 0 }, "rotation" { "w" 0 0, "x" 0 0, "y" 0 0, "z" 0 0 } "timestamp" \<unix timestamp in nano seconds> }, ]