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auto2d_tutorial [2019/07/10 13:33] twagner [Classify] |
auto2d_tutorial [2019/12/10 08:48] twagner |
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- | ====== How to use SPHIRE' | + | ====== How to use SPHIRE' |
+ | This tutorial describes how to use Cinderella to classify 2D class averages. You can either use a pretrained model (see section // | ||
==== Download & Install ==== | ==== Download & Install ==== | ||
You can find the download and installation instructions here: [[auto_2d_class_selection|Download and Installation]] | You can find the download and installation instructions here: [[auto_2d_class_selection|Download and Installation]] | ||
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I suppose you downloaded the latest classification model. | I suppose you downloaded the latest classification model. | ||
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- | This is the corresponding configuration file: | ||
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- | <code json config.json> | ||
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- | The fields have the following meaning: | ||
- | * asdasd | ||
- | * azxczxc | ||
- | * bnnvb | ||
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- | Copy this into a new file called '' | ||
To run the classification I suppose you want to separate good and bad classes in classes_after_isac.hdf (or any other .mrcs / .hdf file with classes) and you want to save your new .hdf (.mrcs) files into the folder '' | To run the classification I suppose you want to separate good and bad classes in classes_after_isac.hdf (or any other .mrcs / .hdf file with classes) and you want to save your new .hdf (.mrcs) files into the folder '' | ||
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- | sp_cinderella_predict.py -i path/ | + | sp_cinderella_predict.py -i path/ |
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} | } |