Skip to main content

StarDist

Project description

StarDist

The code in this repository implements object detection with star-convex polygons as described in the paper:

Uwe Schmidt, Martin Weigert, Coleman Broaddus, and Gene Myers.
Cell Detection with Star-convex Polygons.
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Granada, Spain, September 2018.

Please cite the paper if you are using this code in your research.

@inproceedings{schmidt2018,
  author    = {Uwe Schmidt and Martin Weigert and Coleman Broaddus and Gene Myers},
  title     = {Cell Detection with Star-Convex Polygons},
  booktitle = {Medical Image Computing and Computer Assisted Intervention - {MICCAI} 
  2018 - 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part {II}},
  pages     = {265--273},
  year      = {2018},
  doi       = {10.1007/978-3-030-00934-2\_30},
}

Installation

This package requires Python 3.5 (or newer) and can be installed with pip:

pip install stardist

Notes

  • Depending on your Python installation, you may need to use pip3 instead of pip.
  • Since this package relies on a C++ extension, you could run into compilation problems (see Troubleshooting below). We currently do not provide pre-compiled binaries.
  • StarDist uses the deep learning library Keras, which requires a suitable backend (we only tested TensorFlow).

Usage

We provide several Jupyter notebooks that illustrate how this package can be used.

Troubleshooting

Installation requires Python 3.5 (or newer) and a working C++ compiler. We have only tested GCC (macOS, Linux), Clang (macOS), and Visual Studio (Windows 10). Please open an issue if you have problems that are not resolved by the information below.

If available, the C++ code will make use of OpenMP to exploit multiple CPU cores for substantially reduced runtime on modern CPUs. This can be important to prevent the function star_dist (utils.py) from slowing down model training.

macOS

Although Apple provides the Clang C/C++ compiler via Xcode, it does not come with OpenMP support. Hence, we suggest to install the OpenMP-enabled GCC compiler, e.g. via Homebrew with brew install gcc. After that, you can install the package like this (adjust names/paths as necessary):

CC=/usr/local/bin/gcc-8 CXX=/usr/local/bin/g++-8 pip install stardist

Windows

Please install the Build Tools for Visual Studio 2017 from Microsoft to compile extensions for Python 3.5 and 3.6 (see this for further information). During installation, make sure to select the Visual C++ build tools. Note that the compiler comes with OpenMP support.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

stardist-0.2.0.tar.gz (58.8 kB view details)

Uploaded Source

File details

Details for the file stardist-0.2.0.tar.gz.

File metadata

  • Download URL: stardist-0.2.0.tar.gz
  • Upload date:
  • Size: 58.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.1.0 requests-toolbelt/0.8.0 tqdm/4.19.5 CPython/3.6.4

File hashes

Hashes for stardist-0.2.0.tar.gz
Algorithm Hash digest
SHA256 a639ba2d5d09a195beb1f7e847cf0c5fee15e0013d014bcdee8eb81bfab2a838
MD5 2924e161fa478c4219de74b2a06f8d3a
BLAKE2b-256 77b9e5c25dc38b4b993b9c52aff6130a354350a924171390b8b56a96e01a97e2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page