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auto_2d_class_selection [2019/07/11 14:01] twagner [Pretrained model] |
auto_2d_class_selection [2020/08/27 13:04] fschoenfeld |
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- | ====== Cinderella: | + | ====== Cinderella: |
---- | ---- | ||
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---- | ---- | ||
+ | Our binary classification | ||
+ | Cinderella supports '' | ||
+ | // | ||
+ | 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, | ||
- | 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. | ||
< | < | ||
- | * **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:// | ||
{{ :: | {{ :: | ||
- | ====== The 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: 0.3.0 | + | 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 version | + | Old versions |
====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 === | ||
+ | * Balances unbalanced training datasets. | ||
+ | * It is now possible to train Cinderella to select micrographs | ||
+ | * Updated the general model for 2D class selection. | ||
+ | |||
+ | === 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 === | === Version 0.3.0 === | ||
* More data augmentation (add rotation) | * More data augmentation (add rotation) | ||
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After that, create a new virtual environment: | After that, create a new virtual environment: | ||
< | < | ||
- | conda create -n cinderella -c anaconda python=3.6 pyqt=5 cudnn=7.1.2 | + | conda create -n cinderella -c anaconda python=3.6 pyqt=5 cudnn=7.1.2 |
</ | </ | ||
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< | < | ||
source activate cinderella | source activate cinderella | ||
- | </ | ||
- | |||
- | Install fast numpy: | ||
- | < | ||
- | conda install numpy==1.15.4 | ||
</ | </ | ||
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====== Tutorial ====== | ====== Tutorial ====== | ||
- | [[auto2d_tutorial|We created a tutorial how to use Cinderella!]] | + | We created three tutorials: |
+ | |||
+ | * [[auto2d_tutorial|How to use Cinderella for 2D class selection]] | ||
+ | * [[cinderella_micrographs|How to use Cinderella for micrograph selection]] | ||
+ | * [[cinderella_tomograms|How | ||
+ |