CLI utilities for working with N5 files.
Written in Rust using the Rust N5 crate.
$ cargo install n5gest $ n5gest -h n5gest 0.3.9 Andrew Champion <email@example.com> Utilities for N5 files. USAGE: n5gest [OPTIONS] <SUBCOMMAND> FLAGS: -h, --help Prints help information -V, --version Prints version information OPTIONS: -t, --threads <threads> Number of threads for parallel processing. By default, the number of CPU cores is used. SUBCOMMANDS: bench-read Benchmark reading an entire dataset. cast Cast an existing dataset into a new dataset with a given data type. crop-blocks Crop wrongly sized blocks to match dataset dimensions at the end of a given axis. delete-uniform-blocks Delete blocks uniformly filled with a given value, such as empty blocks. export Export a sequence of image files from a series of z-sections. help Prints this message or the help of the given subcommand(s) import Import a sequence of image files as a series of z-sections into a 3D N5 dataset. import-tiff Import a single file TIFF stack as a series of z-sections into a 3D N5 dataset ls List all datasets under an N5 root. map Run simple math expressions mapping values to new datasets. For example, to clip values in a dataset: `map example.n5 dataset_in example.n5 dataset_out "min(128, x)"` Note that this converts back and forth to `f64` for the calculation. map-fold Run simple math expressions as folds over blocks. For example, to find the maximum value in a positive dataset: `map-fold example.n5 dataset 0 "max(acc, x)"` recompress Recompress an existing dataset into a new dataset with a given compression. slice-img Export a 2D subslice of an ND dataset to an image file. For exporting sequences of images see `export` stat Retrieve metadata about the number of blocks that exists and their timestamps. validate-blocks Report malformed blocks.
Licensed under either of
- Apache License, Version 2.0, (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.