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msgid"Download at least one RunCellpose Docker and one ilastik Docker from Dockerhub. This will happen automatically the first time you call a given Docker from CellProfiler (i.e. run a CellProfiler pipeline that uses the Docker) but if you are running this tutorial in a workshop setting we strongly recommend download in advance of the workshop as these are large files (5-10 GB) and bandwidth is often limited in a workshop setting. In Docker Desktop or Podman Desktop you can search for containers in the top search bar (see below). Make sure you select a tag (version) that is supported by the plugin you are using and then select \"Pull\". We reccomend `biocontainers/ilastik:1.4.0_cv2` for ilastik and `cellprofiler/runcellpose_with_pretrained:3.1.2.2` or `cellprofiler/runcellpose_with_pretrained:4.0.6` for Cellpose."
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msgid"Download at least one RunCellpose Docker and one ilastik Docker from Dockerhub. This will happen automatically the first time you call a given Docker from CellProfiler (i.e. run a CellProfiler pipeline that uses the Docker) but if you are running this tutorial in a workshop setting we strongly recommend download in advance of the workshop as these are large files (5-10 GB) and bandwidth is often limited in a workshop setting. In Docker Desktop or Podman Desktop you can search for containers in the top search bar (see below). Make sure you select a tag (version) that is supported by the plugin you are using and then select \"Pull\". We recommend `biocontainers/ilastik:1.4.0_cv2` for ilastik and `cellprofiler/runcellpose_with_pretrained:3.1.2.2` for Cellpose."
msgid"You may wish to put a pause <img src=\"./TutorialImages/Pause.png\" width=\"20\" alt=\"Pause\"/> next to SaveImages, or uncheck it <img src=\"./TutorialImages/InactivatedModule.png\" width=\"20\" alt=\"Unchecked\"/>, to keep it from saving images while you are exploring this pipeline."
msgid"If using Docker, the very first time you execute the RunCellpose module, it will need to download a ~5GB-10GB file (depending on the verison of Cellpose), which may be slow depending on your internet connection (unless you downloaded it in preparation as we suggest above). You only need to do this step once, however!"
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msgid"If using Docker/Podman, the very first time you execute the RunCellpose module, it will need to download a ~5GB-10GB file (depending on the verison of Cellpose), which may be slow depending on your internet connection (unless you downloaded it in preparation as we suggest above). You only need to do this step once, however!"
msgid"Put CellProfiler into TestMode <img src=\"./TutorialImages/startTestMode.png\" width=\"120\" alt=\"Start Test Mode button\"/>, open the eye icons <img src=\"./TutorialImages/EyeOpen.png\" width=\"20\" alt=\"Open Eye icon\"/> next to RunCellpose and OverlayOutlines, and then hit Run <img src=\"./TutorialImages/Run.png\" width=\"120\" alt=\"Run\"/>"
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msgid"Put CellProfiler into TestMode <img src=\"./TutorialImages/startTestMode.png\" width=\"120\" alt=\"Start Test Mode button\"/>"
msgid"If using Docker/Podman, and if you've already pre-downloaded a container, ensure that the `Select Cellpose Docker image` setting in the `RunCellpose` module matches the container you already downloaded."
msgid"Open the eye icons <img src=\"./TutorialImages/EyeOpen.png\" width=\"20\" alt=\"Open Eye icon\"/> next to RunCellpose and OverlayOutlines, and then hit Run <img src=\"./TutorialImages/Run.png\" width=\"120\" alt=\"Run\"/>"
msgid"As before, using OverlayOutlines and/or the WorkspaceViewer, evaluate segmentation on a few images. Where is CellProfiler doing better, and where is Cellpose doing better?"
msgid"Use the Info <img src=\"./TutorialImages/Info.png\" width=\"35\" alt=\"Info\"/> button to learn more about the different parameters you can pass to Cellpose (we don't offer all of them, but many!) - how does tweaking these affect your output? How about changing the model you're using, and/or the image you're segmenting?"
msgid"The data we gave you in this exercise was all very clean, and all from the negative control wells of this experiment. The [folder linked here](https://drive.google.com/file/d/10kZMhr2bVR14vMP7kG5iZGujjUI3Nn3Y/view?usp=sharing) contains images with a broader variety of phenotypes - try replacing the images in the `Images` module with this folder instead and see how well the two kinds of segmentation work in different conditions!"
msgid"You’re encouraged to explore the performance in some random images on your own (you can do this from the `Test` menu with the `Random Image Set` option), but if you find yourself consistently ending up with images that look similar you can try examining images from the following list of wells- A08, A12, B12, B18, C7, D6, D19, D22, E3. You can pick these with `Test` -> `Choose Image Set`"
msgid"Based on your evaluations above, can you identify some places where additional training might help fix some issues in the Cellpose model? If you happen to have Cellpose on your computer (or want to try installing it - see Exercise 1 for a link to the official install instructions), open Cellpose with some of the `Ch1` images and see if you can train a model that will perform better."
msgid"The classical segmentation parameters provided here are based on expert tuning from a very experienced CellProfiler user - how close can you get? Add another IdentifyPrimaryObjects module to the pipeline, tune it yourself, and then look in the workspace viewer to see how it performs, especially in the more diverse image set from Bonus-to-the-Bonus 1. Compare your parameters to the expert ones - how do they differ? Do you understand why some of these settings may have been chosen?"
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