deploy: 662bb00

_sources/supported_plugins.md

@@ -3,15 +3,15 @@
 Below is a brief overview of our currently supported plugins.
 For details about using any particular plugin, please read the module documentation inside the plugin in CellProfiler.
 
-Most plugins will run without any special installation of either CellProfiler or the plugins. 
+Most plugins will run without any special installation of either CellProfiler or the plugins.
 See [using plugins](using_plugins.md) for how to set up CellProfiler for plugin use as well as for installation information for those plugins that do require installation of dependencies.
 
 Most plugin documentation can be found within the plugin itself and can be accessed through CellProfiler help.
 Those plugins that do have extra documentation contain links below.
 
-
 | Plugin | Description | Requires installation of dependencies? | Install flag | Docker version currently available? |
 |--------|-------------|----------------------------------------|--------------|-------------------------------------|
+| AddNoise      | AddNoise adds Gaussian, Poisson, or Salt and Pepper noise to images. Of particular use for data augmentation in deep learning. | No | | N/A |
 | CalculateMoments      | CalculateMoments extracts moments statistics from a given distribution of pixel values. | No | | N/A |
 | CallBarcodes          | CallBarcodes is used for assigning a barcode to an object based on the channel with the strongest intensity for a given number of cycles. It is used for optical sequencing by synthesis (SBS). | No | | N/A |
 | CompensateColors      | CompensateColors determines how much signal in any given channel is because of bleed-through from another channel and removes the bleed-through. It can be performed across an image or masked to objects and provides a number of preprocessing and rescaling options to allow for troubleshooting if input image intensities are not well matched. | No | | N/A |
@@ -21,7 +21,7 @@ Those plugins that do have extra documentation contain links below.
 | HistogramMatching     | HistogramMatching manipulates the pixel intensity values an input image and matches them to the histogram of a reference image. It can be used as a way to normalize intensities across different 2D or 3D images or different frames of the same 3D image. It allows you to choose which frame to use as the reference. | No | | N/A |
 | PixelShuffle          | PixelShuffle takes the intensity of each pixel in an image and randomly shuffles its position. | No | | N/A |
 | [RunCellpose](RunCellPose.md) | RunCellpose allows you to run Cellpose within CellProfiler. Cellpose is a generalist machine-learning algorithm for cellular segmentation and is a great starting point for segmenting non-round cells. You can use pre-trained Cellpose models or your custom model with this plugin. You can use a GPU with this module to dramatically increase your speed/efficiency. | Yes | `cellpose` | Yes |
-| Runilastik            | Runilasitk allows to run ilastik within CellProfiler. You can use pre-trained ilastik projects/models to predict the probability of your input images. The plugin supports two types of ilastik projects: Pixel Classification and Autocontext (2-stage).| Yes |  | Yes | 
+| Runilastik            | Runilasitk allows to run ilastik within CellProfiler. You can use pre-trained ilastik projects/models to predict the probability of your input images. The plugin supports two types of ilastik projects: Pixel Classification and Autocontext (2-stage).| Yes |  | Yes |
 | RunImageJScript       | RunImageJScript allows you to run any supported ImageJ script directly within CellProfiler. It is significantly more performant than RunImageJMacro, and is also less likely to leave behind temporary files. | Yes | `imagejscript` , though note that conda installation may be preferred, see [this link](https://py.imagej.net/en/latest/Install.html#installing-via-pip) for more information | No |
 | RunOmnipose           | RunOmnipose allows you to run Omnipose within CellProfiler. Omnipose is a general image segmentation tool that builds on Cellpose. | Yes | `omnipose` | No |
 | RunStarDist           | RunStarDist allows you to run StarDist within CellProfiler. StarDist is a machine-learning algorithm for object detection with star-convex shapes making it best suited for nuclei or round-ish cells. You can use pre-trained StarDist models or your custom model with this plugin. You can use a GPU with this module to dramatically increase your speed/efficiency. RunStarDist is generally faster than RunCellpose. | Yes | `stardist` | No |