This shows you the differences between two versions of the page.
Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
cinderella_tomograms [2019/12/13 15:01] twagner [Training] |
cinderella_tomograms [2019/12/13 15:17] twagner [Training] |
||
---|---|---|---|
Line 32: | Line 32: | ||
</ | </ | ||
- | Path the following configuration and adapt it for your needs. The only things | + | Copy the following configuration |
<code json config.json> | <code json config.json> | ||
Line 66: | Line 66: | ||
< | < | ||
- | sp_cinderella_train.py -c example_config.json --gpu 1 | + | sp_cinderella_train.py -c config.json --gpu 1 |
</ | </ | ||
- | This will train a classification network on the GPU with ID=1. After the training finishes, you get a '' | + | This will train a classification network on the GPU with ID=1. After the training finishes, you get a '' |
Line 75: | Line 75: | ||
==== Prediction ==== | ==== Prediction ==== | ||
+ | To run the prediction on ' | ||
+ | |||
+ | < | ||
+ | sp_cinderella_predict.py -i my_subtomograms.hdf -w my_model.h5 -o output_folder/ | ||
+ | </ | ||
+ | |||
+ | You will find two new mrcs files with the classified subtomograms. To check the results with e2display, you have to extract the central slices again (see [[cinderella_tomograms# | ||