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--- janni_tutorial [2019/09/16 11:17]
twagner [Denoise]
+++ janni_tutorial [2019/09/16 13:22]
shaikh [Start JANNI]
@@ Line 4: / Line 4: @@
 [[https://arxiv.org/abs/1803.04189|Noise2Noise: Learning Image Restoration without Clean Data - arXiv]]
-JANNI can be used a command line tool but also provides an simple interface to be integrated into other programs.
+Besides a simple GUI and a commandline interface, JANNI also provides an simple python interface to be integrated into other programs.
 ==== Download and Installation ====
@@ Line 15: / Line 15: @@
 </code>
-You can use JANNI either by command line or with the GUI. Typically, most users prefer to use the GUI (but we will also provide the command line commands in this tutorial). You can start the GUI with
+You can use JANNI either by command line or with the GUI. Typically, most users prefer to use the GUI (but we will also provide the command line commands in this tutorial). You can start the GUI with:
 <code>
 janni_denoise.py
 </code>
-The GUI is basically a visualization of the command line interface:
+The GUI is essentially a visualization of the command line interface:
 {{ ::start_01.png?700 |}}
@@ Line 29: / Line 29: @@
   * **denoise**: Run this action to apply a model on new images.
-Each action has several parameters which are organized in tabs. Once you chosen your settings you can press “Start”, the command will be applied and JANNI shows you the output:
+Each action has several parameters which are organized in tabs. Once you chosen your settings you can press "Start," and the command will be applied and JANNI shows you the output:
 {{ :janni_start_02.png?700 |}}
-It will tell you when something went wrong. Pressing “edit” brings you back to your settings, where you can either edit the settings (in case something went wrong) or go to the next action.
+It will tell you if something goes wrong. Pressing "Edit" brings you back to your settings, where you can either edit the settings (in case something went wrong) or go to the next action.
 ==== Training a model for your data ====
 In case you want to use the general model ([[janni#Download|Download here]]) you can skip this part and directly [[janni_tutorial#denoise|denoise]] your images.

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