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cinderella_micrographs [2019/12/10 09:20]
twagner [Training]
cinderella_micrographs [2020/08/28 07:34]
twagner [Training]
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 The first step is to train Cinderella with manually selected good and bad micrographs. Create two folders, one containing manually selected good micrographs (e.g ''GOOD_MICS/'') and one contain bad micrographs (e.g ''BAD_MICS/''). Both folders can contain subfolders. The first step is to train Cinderella with manually selected good and bad micrographs. Create two folders, one containing manually selected good micrographs (e.g ''GOOD_MICS/'') and one contain bad micrographs (e.g ''BAD_MICS/''). Both folders can contain subfolders.
 +<note question>
 +**How many micrographs do I need?**
 +
 +We typically start with 30 good and 30 bad micrographs.
 +</note>
  
 Then specify the paths into a config file like this: Then specify the paths into a config file like this:
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 } }
 </code> </code>
-The fields have the following meaning:+The fields in the section **model** have the following meaning:
   * **input_size**: This is the image size to which each micrograph is resized to.   * **input_size**: This is the image size to which each micrograph is resized to.
-  * **batch_size**: How many micrograph are in one mini-batch. If you have memory problems, you can try to reduce this value.+  * **mask_radius**: (Optional) Circular mask radius which is applied after resizing to the input size. If not given is 0.4*input_size. 
 + 
 +The fields in the section **train** have the following meaning: 
 +  * **batch_size**: How many micrographs are in one mini-batch. If you have memory problems, you can try to reduce this value.
   * **good_path**: Path to folder with good micrographs.   * **good_path**: Path to folder with good micrographs.
   * **bad_path**: Path to folder with bad micrographs.   * **bad_path**: Path to folder with bad micrographs.
cinderella_micrographs.txt · Last modified: 2020/08/28 07:35 by twagner