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auto_2d_class_selection [2019/12/10 09:35] twagner [Tutorial] |
auto_2d_class_selection [2020/08/27 13:44] twagner |
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- | ====== Cinderella: Deep learning based 2D class and micrograph selection | + | ====== Cinderella: Deep learning based binary classification tool ====== |
---- | ---- | ||
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---- | ---- | ||
- | + | Our binary classification | |
- | Our 2d class and micrograph selection | + | Cinderella |
- | For 2D classes, it supports .hdf/ | + | //Cinderella// was written to automate cryo-em data processing. |
- | Cinderella | + | We provide a pretrained general model for classifying class averages |
< | < | ||
- | * **License**: | + | * **License**: |
- | * **GitHub repository**: https:// | + | * **Repository**: [[https:// |
</ | </ | ||
- | Here are a couple of examples for good / bad classes in Cinderella: | + | |
+ | ====== 2D class selection model ====== | ||
+ | Our model was trained on a set of 2D classes from both [[https:// | ||
{{ :: | {{ :: | ||
- | ====== 2D class selection model ====== | + | |
- | 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?" | + | |
- | <note important> | + | |
- | The training dataset does **not contain any Relion classes**, so it might be that Cinderella will not work with well them. | + | |
- | </ | + | |
You can easily [[auto_2d_class_selection# | You can easily [[auto_2d_class_selection# | ||
- | Right now our model is trained on **19 datasets**. But we will increase the number often! | + | Right now our model is trained on **4773 good classes and 5390 bad classes**. |
====== Download ====== | ====== Download ====== | ||
====Cinderella==== | ====Cinderella==== | ||
- | Version: 0.4.0 | + | Version: 0.7.0 |
- | Uploaded: | + | Uploaded: |
[[https:// | [[https:// | ||
- | ====Pretrained model==== | + | ====Pretrained model (2D classes)==== |
- | Uploaded: | + | Uploaded: |
- | + | ||
- | [[ftp://ftp.gwdg.de/ | + | |
- | + | ||
- | [[auto2d_tutorial# | + | |
+ | [[ftp:// | ||
====Archive==== | ====Archive==== | ||
- | Old versions of cinderella and the pretrained model can be found in the [[cinderella_archive|archive]] | + | Old versions of cinderella and the pretrained model can be found in the [[cinderella_archive|archive]]. |
====Changelog==== | ====Changelog==== | ||
+ | |||
+ | === Version 0.7 === | ||
+ | * Now uses a **circular masks by default**. This allows to use full rotation during data augmentation. Can be deactivated by setting the field '' | ||
+ | * The general models now includes **300 new good Relion classes and 2000 new bad Relion classes** (//Thanks to Grigory Sharov//). | ||
+ | * Fixed numerical instability that occurs when you have classes filled with a constant value (//Thanks to Grigory Sharov//). | ||
+ | * Fixed a problem with classes that contain NaN values. NaN values are now replaced with 0. (//Thanks to Grigory Sharov//). | ||
+ | * Fixed an issue when filenames contain more than one point. | ||
+ | |||
+ | === Version 0.6 === | ||
+ | * Fix an issue for classes in mrcs format | ||
+ | * Minor changes | ||
+ | |||
+ | === Version 0.5 === | ||
+ | * Add support for subtomograms | ||
+ | * Faster file reading | ||
+ | |||
=== Version 0.4 === | === Version 0.4 === | ||
- | * Apply weights if good / bad training classes are unbalanced | + | * Balances |
- | * It is now possible to train cinderella | + | * It is now possible to train Cinderella |
* Updated the general model for 2D class selection. | * Updated the general model for 2D class selection. | ||
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====== Tutorial ====== | ====== Tutorial ====== | ||
- | We created | + | We created |
* [[auto2d_tutorial|How to use Cinderella for 2D class selection]] | * [[auto2d_tutorial|How to use Cinderella for 2D class selection]] | ||
* [[cinderella_micrographs|How to use Cinderella for micrograph selection]] | * [[cinderella_micrographs|How to use Cinderella for micrograph selection]] | ||
+ | * [[cinderella_tomograms|How to use Cinderella for subtomogram selection]] | ||