Skip to main content
`Ctrl`+`K`

# Quickstart

## Importing dask-image

Import dask image is with an underscore, like this example:

    import dask_image.imread
    import dask_image.ndfilters

## Dask Examples

We highly recommend checking out the dask-image-quickstart.ipynb notebook (and any other dask-image example notebooks) at the dask-examples repository. You can find the dask-image quickstart notebook in the `applications` folder of this repository:

dask/dask-examples

The direct link to the notebook file is here:

dask/dask-examples

All the example notebooks are available to launch with mybinder and test out interactively.

## An Even Quicker Start

You can read files stored on disk into a dask array by passing the filename, or regex matching multiple filenames into `imread()`.

    filename_pattern = 'path/to/image-*.png'
    images = dask_image.imread.imread(filename_pattern)

If your images are parts of a much larger image, dask can stack, concatenate or block chunks together: http://docs.dask.org/en/latest/array-stack.html

Calling dask-image functions is also easy.

    import dask_image.ndfilters
    blurred_image = dask_image.ndfilters.gaussian_filter(images, sigma=10)

Many other functions can be applied to dask arrays. See the dask_array_documentation for more detail on general array operations.

    result = function_name(images)

## Further Reading

Good places to start include:

- The dask-image API documentation: http://image.dask.org/en/latest/api.html

- The documentation on working with dask arrays: http://docs.dask.org/en/latest/array.html

## Talks and Slides

Here are some talks and slides that you can watch to learn dask-image:

- 2020, Genevieve Buckley’s talk at PyConAU and SciPy Japan

  - Watch the talk

  - Scipy Japanのトークを見る(プレゼンテーション:英語, 字幕:日本語) Watch the talk at SciPy Japan (presentation in English, captions in Japanese)

  - See the slides

- 2019, John Kirkham’s SciPy talk

  - Watch the talk here

  - See the slides here