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--- janni_tutorial [2019/07/16 10:01]
twagner [Training a model for your data]
+++ janni_tutorial [2019/09/16 09:08]
twagner [Download and Installation]
@@ Line 9: / Line 9: @@
 You can find the download and installation instructions here: [[janni|Download and Installation]]
+==== Start JANNI ====
+ If you followed the installation instructions, you now have to activate the JANNI virtual environment with
+<code>
+source activate janni
+</code>
+You can use JANNI either by command line or with the GUI. Typically, most users prefer to use the GUI. You can start it with
+<code>
+janni_denoise.py
+</code>
 ==== 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.
@@ Line 37: / Line 47: @@
   * **movie_dir**: Path to the directory with the movie files. If an average exists already in even_dir or odd_dir (see below), it will be skipped.
   * **even_dir**: For each movie in movie_dir, an average based on the //even// frames is calculated and saved in even_dir.
-  * **odd_dir**: For each movie in movie_dir, an average based on the //odd// frames is calculated and saved in even_dir.
+  * **odd_dir**: For each movie in movie_dir, an average based on the //odd// frames is calculated and saved in odd_dir.
   * **batch_size**: How many patches are in one mini-batch. If you have memory problems (e.g with cards < 8GB memory), you can try to reduce this value.
   * **learning_rate**: Learning rate, should not be changed.

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