impy

impy is an all-in-one image analysis library, equipped with parallel processing, GPU support, GUI based tools and so on.

Source code

Highlights

  • Automatic parallel batch processing using dask.

  • You don’t have to care about numpy / scipy on CPU, or cupy on GPU. Same code works for both processors.

  • n-D viewing, cropping, image annotation using napari.

  • Easily integrate your custom functions with @ip.bind.

  • Command line usage.

Installation

pip install git+https://github.com/hanjinliu/impy

or

git clone https://github.com/hanjinliu/impy

Contents

Major Classes

Array

blockdiag numpy.ndarray AxesMixin MetaArray LabeledArray PropArray Label ImgArray PhaseArray

  • AxesMixin: An abstract class that axes, scale and shape are defined.

  • PropArray: Array object with properties stored in it. Always made from an ImgArray.

  • Label: Array object of image labels that is attached to ImgArray.

  • ImgArray: Array object with many image processing functions.

  • PhaseArray: Array object with periodic values and specific processing functions.

Array-like

blockdiag AxesMixin LazyImgArray BigImgArray

  • LazyImgArray: Array-like object with image processing functions like ImgArray, but evaluated lazily.

  • BigImgArray: Subclass of LazyImgArray, but images will be processed for every method call.

Data Frame

blockdiag pandas.DataFrame AxesFrame MarkerFrame TrackFrame PathFrame

  • AxesFrame: DataFrame with similar properties as AxesMixin.

  • MarkerFrame: AxesFrame for markers, such as coordinates.

  • TrackFrame: AxesFrame for tracks.

  • PathFrame: AxesFrame for paths.

Indices and tables