119 lines
3.4 KiB
Markdown
119 lines
3.4 KiB
Markdown
# ndbioimage
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[](https://github.com/pomppervova/ndbioimage/actions/workflows/pytest.yml)
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## Work in progress
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Rust rewrite of python version. Read bio image formats using the bio-formats java package.
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[https://www.openmicroscopy.org/bio-formats/](https://www.openmicroscopy.org/bio-formats/)
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Exposes (bio) images as a numpy ndarray-like object (Python) or a struct that can be sliced like an ndarray Array
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(Rust), but without loading the whole image into memory, reading from the file only when needed. Some metadata is read
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and stored in an [ome](https://genomebiology.biomedcentral.com/articles/10.1186/gb-2005-6-5-r47) structure.
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Additionally, it can automatically calculate an affine transform that corrects for chromatic aberrations etc. and apply
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it on the fly to the image.
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Currently, it supports imagej tif files, czi files, micromanager tif sequences and anything
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[bioformats](https://www.openmicroscopy.org/bio-formats/) can handle.
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To transition to semver, versions before 0.1.0 were yanked from crates.io.
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## Installation
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```sh
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pip install ndbioimage
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```
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### Installation with option to write mp4 or mkv:
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Work in progress! Make sure ffmpeg is installed.
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```sh
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pip install ndbioimage[write]
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```
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## Usage
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### Python
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- Reading an image file and plotting the frame at channel=2, time=1
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```python
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import matplotlib.pyplot as plt
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from ndbioimage import Imread
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with Imread('image_file.tif', axes='ctyx', dtype=int) as im:
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plt.imshow(im[2, 1])
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```
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- Showing some image metadata
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```python
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from ndbioimage import Imread
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from pprint import pprint
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with Imread('image_file.tif') as im:
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pprint(im)
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```
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- Slicing the image without loading the image into memory
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```python
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from ndbioimage import Imread
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with Imread('image_file.tif', axes='cztyx') as im:
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sliced_im = im[1, :, :, 100:200, 100:200]
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```
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sliced_im is an instance of Imread which will load any image data from file only when needed
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- Converting (part) of the image to a numpy ndarray
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```python
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from ndbioimage import Imread
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import numpy as np
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with Imread('image_file.tif', axes='cztyx') as im:
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array = np.asarray(im[0, 0])
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```
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### Rust
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```rust
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use ndarray::Array2;
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use ndbioimage::{DynReader, Frame, Reader};
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fn main() -> Result<(), ndbioimage::error::Error> {
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let path = "/path/to/file";
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let reader = DynReader::new(&path, 0, 0)?;
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println!("shape: {}", reader.shape());
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let frame = reader.get_frame(0, 0, 0)?;
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if let Ok(arr) = <Frame as TryInto<Array2<i8>>>::try_into(frame) {
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println!("{:?}", arr);
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} else {
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println!("could not convert Frame to Array<i8>");
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}
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let xml = reader.metadata()?.to_xml()?;
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println!("{}", xml);
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Ok(())
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}
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```
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```rust
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use ndbioimage::{DynReader, Reader};
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fn main() -> Result<(), ndbioimage::error::Error> {
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let path = "/path/to/file";
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let reader = DynReader::new(&path, 0, 0)?;
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let view = reader.view();
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let view = view.max_proj(3)?;
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let array = view.as_array::<u16>()?;
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println!("{:?}", array.shape());
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Ok(())
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}
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```
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### Command line
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```ndbioimage --help```: show help
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```ndbioimage info image```: show metadata about image
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```ndbioimage tiff image image.tif -r```: copy image into image.tif, while registering channels
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```ndbioimage movie image image.mp4 -C cyan lime red``` copy image into image.mp4 (z will be max projected), make channel
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colors cyan lime and red
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