Merge pull request #25 from juglab/develop

Develop

Author: jdeschamps

README.md

@@ -9,26 +9,28 @@
 
 A self-supervised denoising algorithm now usable by all in napari.
 
-![Results](docs/images/noisy_denoised.png)
-
+<img src="https://raw.githubusercontent.com/juglab/napari-n2v/master/docs/images/noisy_denoised.png" width="800" />
 ----------------------------------
 
 ## Installation
-<!---
-You can install `napari-n2v` via [pip]:
 
+You can install `napari-n2v` via [pip]:
+```bash
     pip install napari-n2v
-
+```
 Or through the [napari-hub](https://napari.org/stable/plugins/find_and_install_plugin.html).
--->
-Check out the [documentation](https://juglab.github.io/napari-n2v/installation.html) for installation instructions. (soon on PyPi and napari hub)
+
+
+Check out the [documentation](https://juglab.github.io/napari-n2v/installation.html) for more detailed installation 
+instructions. 
 
 
 ## Quick demo
 
-![Demo prediction](docs/images/demo.gif)
+You can try the quick demo by loading the `N2V Demo prediction` in plugins, and starting the prediction directly.
+
+<img src="https://raw.githubusercontent.com/juglab/napari-n2v/master/docs/images/demo.gif" width="800" />
 
-You can try the quick demo by loading the "N2V Demo prediction" in plugins, and starting the prediction directly.
 
 ## Documentation
 
@@ -43,18 +45,21 @@ help us improve by [filing an issue] along with a detailed description or contac
 through the [image.sc](https://forum.image.sc/) forum (tag @jdeschamps).
 
 
-## Cite us
+## Citations
 
 ### N2V
 
-Krull, Alexander, Tim-Oliver Buchholz, and Florian Jug. "Noise2void-learning denoising from single noisy images." 
+Alexander Krull, Tim-Oliver Buchholz, and Florian Jug. "[Noise2void-learning denoising from single noisy images.](https://ieeexplore.ieee.org/document/8954066)" 
 *Proceedings of the IEEE/CVF conference on computer vision and pattern recognition*. 2019.
 
 ### structN2V
 
-Broaddus, Coleman, et al. "Removing structured noise with self-supervised blind-spot networks." *2020 IEEE 17th 
+Coleman Broaddus, et al. "[Removing structured noise with self-supervised blind-spot networks.](https://ieeexplore.ieee.org/document/9098336)" *2020 IEEE 17th 
 International Symposium on Biomedical Imaging (ISBI)*. IEEE, 2020.
 
+### N2V2
+
+Eva Höck, Tim-Oliver Buchholz, et al. "[N2V2 - Fixing Noise2Void Checkerboard Artifacts with Modified Sampling Strategies and a Tweaked Network Architecture](https://openreview.net/forum?id=IZfQYb4lHVq)", (2022). 
 
 ## Acknowledgements
 

docs/index.md

@@ -6,7 +6,8 @@ removing pixel-independent noise. It also includes an extension, structN2V, aime
 This set of plugins can train, retrain and predict on images from napari or from the disk. It conveniently allows saving 
 the models for later use and is compatible with [Bioimage.io](https://bioimage.io/#/). 
 
-![napari-n2v](images/training.gif)
+
+<img src="https://raw.githubusercontent.com/juglab/napari-n2v/master/docs/images/training.gif" width="800" />
 
 # Documentation
 
@@ -20,18 +21,22 @@ the models for later use and is compatible with [Bioimage.io](https://bioimage.i
 Help us improve the plugin by submitting [issues to the Github repository](https://github.com/juglab/napari-n2v/issues) 
 or tagging @jdeschamps on [image.sc](https://forum.image.sc/). 
 
-# Cite us
+# Citation
 
-## N2V
+### N2V
 
-Krull, Alexander, Tim-Oliver Buchholz, and Florian Jug. "Noise2void-learning denoising from single noisy images." 
+Alexander Krull, Tim-Oliver Buchholz, and Florian Jug. "[Noise2void-learning denoising from single noisy images.](https://ieeexplore.ieee.org/document/8954066)" 
 *Proceedings of the IEEE/CVF conference on computer vision and pattern recognition*. 2019.
 
-## structN2V
+### structN2V
 
-Broaddus, Coleman, et al. "Removing structured noise with self-supervised blind-spot networks." *2020 IEEE 17th 
+Coleman Broaddus, et al. "[Removing structured noise with self-supervised blind-spot networks.](https://ieeexplore.ieee.org/document/9098336)" *2020 IEEE 17th 
 International Symposium on Biomedical Imaging (ISBI)*. IEEE, 2020.
 
+### N2V2
+
+Eva Höck, Tim-Oliver Buchholz, et al. "[N2V2 - Fixing Noise2Void Checkerboard Artifacts with Modified Sampling Strategies and a Tweaked Network Architecture](https://openreview.net/forum?id=IZfQYb4lHVq)", (2022).
+
 
 # Support 
 

setup.cfg

@@ -1,9 +1,9 @@
 [metadata]
 name = napari-n2v
-version = 0.0.1
+version = 0.0.2
 author = Tom Burke, Joran Deschamps
 author_email = joran.deschamps@fht.org
-url = https://github.com/githubuser/napari-n2v
+url = https://github.com/juglab/napari-n2v
 license = BSD-3-Clause
 description = A self-supervised denoising algorithm now usable by all in napari.
 long_description = file: README.md
@@ -19,13 +19,14 @@ classifiers =
     Programming Language :: Python :: 3.7
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
+    Programming Language :: Python :: 3.10
     Operating System :: OS Independent
     License :: OSI Approved :: BSD License
 project_urls =
-    Bug Tracker = https://github.com/githubuser/napari-n2v/issues
+    Bug Tracker = https://github.com/juglab/napari-n2v/issues
     Documentation = https://juglab.github.io/napari-n2v/
-    Source Code = https://github.com/githubuser/napari-n2v
-    User Support = https://github.com/githubuser/napari-n2v/issues
+    Source Code = https://github.com/juglab/napari-n2v
+    User Support = https://github.com/juglab/napari-n2v/issues
 
 [options]
 packages = find: