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auto_2d_class_selection [2019/05/28 22:19] twagner [Cinderella: Automatic 2D class selection] |
auto_2d_class_selection [2020/08/27 15:11] twagner [Changelog] |
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- | ====== Cinderella: | + | ====== Cinderella: |
- | 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 | + | ---- |
+ | < | ||
+ | < | ||
+ | <p align=" | ||
+ | </ | ||
+ | ---- | ||
- | | + | Our binary classification |
- | | + | Cinderella supports '' |
+ | //Cinderella// was written to automate cryo-em data processing. | ||
+ | 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, | ||
- | {{ ::cinderella_example.jpg? | + | < |
+ | * **License**: [[https://github.com/ | ||
+ | * **Repository**: | ||
+ | </ | ||
- | ====== 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# | ||
- | Right now our model is trained on **17 datasets**. But we will increase the number often! | + | ====== 2D class selection model ====== |
+ | Our model was trained on a set of 2D classes from both [[https:// | ||
+ | |||
+ | {{ :: | ||
+ | |||
+ | |||
+ | You can easily [[auto_2d_class_selection# | ||
+ | |||
+ | Right now our model is trained on **4773 good classes and 5390 bad classes**. | ||
====== Download ====== | ====== Download ====== | ||
====Cinderella==== | ====Cinderella==== | ||
- | Version: 0.2.0 | + | Version: 0.7.0 |
- | Uploaded: | + | Uploaded: |
- | [[ftp://ftp.gwdg.de/pub/misc/sphire/ | + | [[https://pypi.org/project/cinderella/#files|DOWNLOAD]] |
- | ====Pretrained model==== | + | ====Pretrained model (2D classes)==== |
- | Uploaded: | + | Uploaded: |
- | [[ftp:// | + | [[ftp:// |
+ | ====Archive==== | ||
+ | Old versions of cinderella and the pretrained model can be found in the [[cinderella_archive|archive]]. | ||
- | [[auto2d_tutorial# | + | ====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 Takanori Nakane and 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 === | ||
+ | * 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 | ||
====== Contribute ====== | ====== Contribute ====== | ||
Here is the repository of our training data: | Here is the repository of our training data: | ||
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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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</ | </ | ||
- | Install Cinderella: | + | Install Cinderella |
< | < | ||
- | conda install numpy==1.14.5 | + | pip install cinderella[gpu] |
- | pip install cinderella-X.Y.Z.tar.gz | + | </ |
+ | **... or CPU**: | ||
+ | < | ||
+ | pip install cinderella[cpu] | ||
</ | </ | ||
====== Tutorial ====== | ====== Tutorial ====== | ||
- | [[auto2d_tutorial|We created a tutorial how to use and train 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 | ||
+ |