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auto_2d_class_selection [2019/12/16 10:44]
twagner [Cinderella: Deep learning based binary classification tool]
auto_2d_class_selection [2019/12/16 14:07]
twagner [Cinderella: Deep learning based binary classification tool]
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 Our binary classification  tool (**Cinderella**) is based on a deep learning network to classify class averages, micrographs or subtomograms into good and bad categories. Our binary classification  tool (**Cinderella**) is based on a deep learning network to classify class averages, micrographs or subtomograms into good and bad categories.
 For class averages, it supports .hdf/.mrcs, for micrographs .mrc format and for subtomograms it expect that they are saved in a .hdf file. For class averages, it supports .hdf/.mrcs, for micrographs .mrc format and for subtomograms it expect that they are saved in a .hdf file.
-Cinderella provides a pretrained general model for classifying 2D classes and was written to automate cryo-em data processing. It's open source and easy to use ([[auto2d_tutorial|see tutorial]]). You can easily train it with your own set of classes/micrographs.+Cinderella was written to automate cryo-em data processing.  It's open source and easy to use
 +We provide a pretrained general model for classifying class averages.([[auto2d_tutorial|see tutorial]]). But you can easily train it with your own set of classes/micrographs/subtomograms.
  
 <note> <note>
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 </note> </note>
  
-Here are a couple of examples for good / bad classes in Cinderella:  
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-{{ ::cinderellea.png?450 |}} 
  
 ====== 2D class selection model ====== ====== 2D class selection model ======
auto_2d_class_selection.txt · Last modified: 2020/08/27 15:11 by twagner