auto_2d_class_selection

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auto_2d_class_selection [2019/06/06 12:26]
twagner [Cinderella: Automatic 2D class selection]
auto_2d_class_selection [2019/07/29 14:48] (current)
twagner [Changelog]
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 Our automatic 2d class selection tool (**Cinderella**) is based on a deep learning network to seperate 2D classes from .hdf / .mrcs files into good and bad classes. It uses the same deep neural network as crYOLO and was pretrained on a set good / bad classes. Cinderella 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. Our automatic 2d class selection tool (**Cinderella**) is based on a deep learning network to seperate 2D classes from .hdf / .mrcs files into good and bad classes. It uses the same deep neural network as crYOLO and was pretrained on a set good / bad classes. Cinderella 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.
 +<​note>​
   * **License**:​ MIT   * **License**:​ MIT
   * **GitHub repository**:​ https://​github.com/​MPI-Dortmund/​sphire_classes_autoselect   * **GitHub repository**:​ https://​github.com/​MPI-Dortmund/​sphire_classes_autoselect
 +</​note>​
 Here are a couple of examples for good / bad classes in Cinderella: ​ Here are a couple of examples for good / bad classes in Cinderella: ​
  
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 ====== The Model ====== ====== The Model ======
-Our model was trained on a set of 2D classes from ISAC. The training dataset does **not contain any Relion classes**, so it might be that Cinderella will not work with them. However, you can easily [[auto_2d_class_selection#​contribute|contribute]]!  ​During the creation of the training dataset, I tried to ask myself "Which class would I select If I would not know the particle?"​ to decide which is a good class.+Our model was trained on a set of 2D classes from ISAC. During the creation of the training dataset, I tried to ask myself "Which class would I select If I would not know the particle?"​ to decide which is a good class. 
 +<note important>​ 
 +The training dataset does **not contain any Relion classes**, so it might be that Cinderella will not work with well them. 
 +</​note>​ 
 +You can easily [[auto_2d_class_selection#​contribute|contribute]] ​your own classes!  ​
  
-Right now our model is trained on **17 datasets**. But we will increase the number often!+Right now our model is trained on **19 datasets**. But we will increase the number often!
 ====== Download ====== ====== Download ======
 ====Cinderella==== ====Cinderella====
-Version: 0.2.0+Version: 0.3.1
  
-Uploaded: ​28May 2019+Uploaded: ​29July 2019
  
-[[ftp://ftp.gwdg.de/pub/misc/sphire/​cinderella_v0.2.0/​cinderella-0.2.0.tar.gz|DOWNLOAD]]+[[https://pypi.org/project/cinderella/#files|DOWNLOAD]]
  
 ====Pretrained model==== ====Pretrained model====
-Uploaded: ​28May 2019+Uploaded: ​11July 2019, Datasets: 19
  
-[[ftp://​ftp.gwdg.de/​pub/​misc/​sphire/​auto2d_models/​model_cinderella_20190528.h5|DOWNLOAD]]+[[ftp://​ftp.gwdg.de/​pub/​misc/​sphire/​auto2d_models/​model_cinderella_20190708.h5|DOWNLOAD]]
  
 [[auto2d_tutorial#​classify|Valid configuration file]] [[auto2d_tutorial#​classify|Valid configuration file]]
  
 +====Archive====
 +Old version of cinderella and the pretrained model can be found in the [[cinderella_archive|archive]]
 +
 +====Changelog====
 +
 +=== Version 0.3.1 ===
 +  * Downgrade to tensorflow 1.10.1 again, as user report long initialization times
 +  * Only report the number of good / bad classes + their fraction.
 +
 +=== Version 0.3.0 ===
 +  * More data augmentation (add rotation)
 +  * Better sampling of validation data. It is now ensured that each file contributes some validation data.
 +  * Updated tensorflow to 1.12.3 ​ to make it compatible to the crYOLO environment
 ====== Contribute ====== ====== Contribute ======
 Here is the repository of our training data: Here is the repository of our training data:
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 </​code>​ </​code>​
  
-Install ​Cinderella:+Install ​fast numpy:
 <​code>​ <​code>​
-conda install numpy==1.14.5 +conda install numpy==1.15.4 
-pip install cinderella-X.Y.Z.tar.gz ​+</​code>​
  
 +Install Cinderella for **GPU**:
 +<​code>​
 +pip install cinderella[gpu]
 +</​code>​
 +
 +**... or CPU**:
 +<​code>​
 +pip install cinderella[cpu]
 </​code>​ </​code>​
  
 ====== Tutorial ====== ====== Tutorial ======
 [[auto2d_tutorial|We created a tutorial how to use Cinderella!]] [[auto2d_tutorial|We created a tutorial how to use Cinderella!]]
  • auto_2d_class_selection.1559816785.txt.gz
  • Last modified: 2019/06/06 12:26
  • by twagner