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carsen-stringer committed Nov 7, 2022
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![tests](https://github.com/mouseland/cellpose/actions/workflows/test_and_deploy.yml/badge.svg)
[![Coverage Status](https://coveralls.io/repos/github/MouseLand/cellpose/badge.svg?branch=master)](https://coveralls.io/github/MouseLand/cellpose?branch=master)
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[![Downloads](https://pepy.tech/badge/cellpose)](https://pepy.tech/project/cellpose)
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[![Licence: GPL v3](https://img.shields.io/github/license/MouseLand/cellpose)](https://github.com/MouseLand/cellpose/blob/master/LICENSE)
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[![GitHub stars](https://img.shields.io/github/stars/MouseLand/cellpose?style=social)](https://github.com/MouseLand/cellpose/)
[![GitHub forks](https://img.shields.io/github/forks/MouseLand/cellpose?style=social)](https://github.com/MouseLand/cellpose/)

A generalist algorithm for cell and nucleus segmentation.
A generalist algorithm for cell and nucleus segmentation (v1.0) that can be optimized for your own data (v2.0).

Cellpose was written by Carsen Stringer and Marius Pachitariu. To learn about Cellpose 2.0 (human-in-the-loop), read the [paper](https://www.biorxiv.org/content/10.1101/2022.04.01.486764v1) or watch the [talk](https://www.youtube.com/watch?v=3ydtAhfq6H0). To learn about Cellpose 1.0, read the [paper](https://t.co/kBMXmPp3Yn?amp=1) or watch the [talk](https://t.co/JChCsTD0SK?amp=1). For support, please open an [issue](https://github.com/MouseLand/cellpose/issues). Please find the detailed documentation at <span style="font-size:larger;">[cellpose.readthedocs.io](https://cellpose.readthedocs.io/en/latest/)</span>.
Cellpose was written by Carsen Stringer and Marius Pachitariu. To learn about Cellpose 2.0 (human-in-the-loop), read the [paper](https://www.nature.com/articles/s41592-022-01663-4) or watch the [talk](https://www.youtube.com/watch?v=3ydtAhfq6H0). To learn about Cellpose 1.0, read the [paper](https://t.co/kBMXmPp3Yn?amp=1) or watch the [talk](https://t.co/JChCsTD0SK?amp=1). For support, please open an [issue](https://github.com/MouseLand/cellpose/issues). Please find the detailed documentation at <span style="font-size:larger;">[cellpose.readthedocs.io](https://cellpose.readthedocs.io/en/latest/)</span>.

### CITATION

**If you use Cellpose 1 or 2, please cite the Cellpose 1.0 [paper](https://t.co/kBMXmPp3Yn?amp=1):**
Stringer, C., Wang, T., Michaelos, M., & Pachitariu, M. (2021). Cellpose: a generalist algorithm for cellular segmentation. <em>Nature methods, 18</em>(1), 100-106.
([bibtex link](https://scholar.googleusercontent.com/scholar.bib?q=info:rmoKTp0cEiYJ:scholar.google.com/&output=citation&scisdr=CgXHFLYtEMb9qOfkmrg:AAGBfm0AAAAAY2jigrhA_p9qteLfyKDZlh96dZdapgkX&scisig=AAGBfm0AAAAAY2jigv55oXhgKwSArS2sr_fxBh--42gU&scisf=4&ct=citation&cd=-1&hl=en&scfhb=1))
[[bibtex](https://scholar.googleusercontent.com/scholar.bib?q=info:rmoKTp0cEiYJ:scholar.google.com/&output=citation&scisdr=CgXHFLYtEMb9qOfkmrg:AAGBfm0AAAAAY2jigrhA_p9qteLfyKDZlh96dZdapgkX&scisig=AAGBfm0AAAAAY2jigv55oXhgKwSArS2sr_fxBh--42gU&scisf=4&ct=citation&cd=-1&hl=en&scfhb=1)]

**If you use the new human-in-the-loop training or use the new cyto2, livecell, or tissuenet models, please also cite the Cellpose 2.0 [paper](https://www.nature.com/articles/s41592-022-01663-4):**
**If you use the new human-in-the-loop training or use the new cyto2, livecell, or tissuenet models, please also cite the Cellpose 2.0 [paper](https://www.nature.com/articles/s41592-022-01663-4):**
Pachitariu, M. & Stringer, C. (2022). Cellpose 2.0: how to train your own model. <em>Nature methods</em>.

:triangular_flag_on_post: the new tissuenet and livecell models (`tissuenet`, `TN1`, `TN2`, `TN3`, `livecell`, `LC1`, `LC2`, `LC3` and `LC4`) were trained using data under a **CC-BY-NC** license, so these models are **non-commercial use only**.

### :star2: UPDATE v2.0 (April 2022) :star2:
### :star2: v2.0 (April 2022) :star2:

Cellpose 2.0 now allows human-in-the-loop training of models! To learn more...
* Check out the twitter [thread](https://twitter.com/marius10p/status/1511415409047650307?s=20&t=umTVIG1CFKIWHYMrQqFKyQ) for an overview.
* Check out the [preprint](https://www.biorxiv.org/content/10.1101/2022.04.01.486764v1) for more details on the algorithm and the performance.
* Check out the [paper](https://www.nature.com/articles/s41592-022-01663-4) for more details on the algorithm and the performance.
* Watch the short intro [talk](https://www.youtube.com/watch?v=3ydtAhfq6H0) and watch the longer [tutorial talk](https://youtu.be/5qANHWoubZU) which goes through running Cellpose 2.0 in the GUI and a jupyter notebook.
* Check out the full human-in-the-loop [video](https://youtu.be/3Y1VKcxjNy4).
* Check out the colab notebook to get cloud access to a GPU to train your models or run your custom models: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MouseLand/cellpose/blob/main/notebooks/run_cellpose_2.ipynb).
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