Metadata-Version: 2.1
Name: dexp
Version: 2021.4.9.993
Summary: Light-sheet Dataset EXploration and Processing
Home-page: https://github.com/royerlab/dexp
Author: Jordao Bragantini, Ahmet Can Solak, Loic A Royer
Author-email: jordao.bragantini@czbiohub.org, ahmetcan.solak@czbiohub.org, loic.royer@czbiohub.org
License: BSD 3-Clause
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Environment :: GPU :: NVIDIA CUDA :: 11.1
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Image Processing
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.8.0
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.20)
Requires-Dist: scipy
Requires-Dist: numba
Requires-Dist: numcodecs
Requires-Dist: scikit-image
Requires-Dist: tifffile
Requires-Dist: numexpr
Requires-Dist: joblib
Requires-Dist: pytest
Requires-Dist: graphviz
Requires-Dist: click
Requires-Dist: dask
Requires-Dist: dask-image
Requires-Dist: distributed
Requires-Dist: zarr
Requires-Dist: napari[all]
Requires-Dist: cachey
Requires-Dist: gputil
Requires-Dist: gpustat
Requires-Dist: arbol
Requires-Dist: simple-zarr-server
Requires-Dist: requests
Requires-Dist: aiohttp
Requires-Dist: colorcet
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Requires-Dist: PyYAML
Requires-Dist: cairocffi
Provides-Extra: color
Requires-Dist: colorama ; extra == 'color'
Requires-Dist: ansicolors ; extra == 'color'
Provides-Extra: cuda100
Requires-Dist: cupy-cuda100 (==9.0.0b3) ; extra == 'cuda100'
Provides-Extra: cuda101
Requires-Dist: cupy-cuda101 (==9.0.0b3) ; extra == 'cuda101'
Provides-Extra: cuda102
Requires-Dist: cupy-cuda102 (==9.0.0b3) ; extra == 'cuda102'
Provides-Extra: cuda110
Requires-Dist: cupy-cuda110 (==9.0.0b3) ; extra == 'cuda110'
Provides-Extra: cuda111
Requires-Dist: cupy-cuda111 (==9.0.0b3) ; extra == 'cuda111'
Provides-Extra: cuda112
Requires-Dist: cupy-cuda112 (==9.0.0b3) ; extra == 'cuda112'


![fishcolorproj](https://user-images.githubusercontent.com/1870994/113943035-b61b0c00-97b6-11eb-8cfd-ac78e2976ebb.png)
# **dexp** | Light-sheet Dataset EXploration and Processing 

**dexp** is a [napari](https://napari.org/), [CuPy](https://cupy.dev/), [Zarr](https://zarr.readthedocs.io/en/stable/), and [DASK](https://dask.org/) based library for managing, processing and visualizing light-sheet microscopy datasets. It consists in light-sheet specialised image processing functions (equalisation, denoising, dehazing, registration, fusion, stabilization, deskewing, deconvolution), visualization functions (napari-based viewing, 2D/3D rendering, video compositing and resizing, mp4 generation), as well as dataset management functions (copy, crop, concatenation, tiff conversion). Almost all functions are GPU accelerated via [CuPy](https://cupy.dev/) but also have a [numpy](https://numpy.org/)-based fallback option for testing on small datasets. In addition to a functional API, DEXP offers a command line interface that makes it very easy for non-coders to pipeline large processing jobs all the way from a large multi-terabyte raw dataset to fully processed and rendered video in MP4 format. 


## How to install **dexp**

### Prerequisites:

**dexp** works on OSX and Windows, but it is recomended to use the latest version of Ubuntu.
We recommend a machine with a top-of-the-line NVIDIA graphics card (min 12G to be confortable).

First, make sure to have a [working python installation](https://github.com/royerlab/dexp/wiki/Installing-Python) 
Second, make sure to have a compatible and functional [CUDA installation](https://github.com/royerlab/dexp/wiki/Installing-CUDA)

Once these prerequisites are satified, you can install **dexp**.

### Installation:

**dexp** can simply be installed with:

To installs **dexp** with GPU support (CUDA 11.2) and colored console output do:
```
pip install dexp[color, cuda112]
```
Other available CUDA versions (from [CuPy](https://cupy.dev/)) are: cuda111, cuda110, cuda102, cuda101, cuda100.

If instead you do not wish to add CUDA support, you can instead do:
```
pip install dexp
```

**For OSX users:** Before installating dexp, you will first need to install cairo:
```
brew install cairo
```

### Quick one-line environment setup and installation:

The following line will delete any existing dexp environment, recreate it, and install **dexp** with support for CUDA 11.2:
```
conda deactivate; conda env remove --name dexp; conda create -y --name dexp python=3.8; conda activate dexp; pip install dexp[color,cuda112]
```

### Leveraging extra CUDA libraries for faster processing:

If you want you **dexp** CUDA-based processing to be even faster, you can install additional libraries such as CUDNN and CUTENSOR 
with the following command:

```
install cudalibs 11.2
```
Change the CUDA version accordingly...

### How to use **dexp** ?

First you need a dataset aqquired on a light-sheet microscope, see [here](https://github.com/royerlab/dexp/wiki/dexp_datasets) for supported microscopes and formats.

Second, you can use any of the commands [here](https://github.com/royerlab/dexp/wiki/dexp_commands) to process your data.
The list of commands can be found by :

```
dexp --help
```


### Example usage























