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The documentation has moved to https://cryolo.readthedocs.io/en/latest/
Here you can find how to apply the general models we trained for you. If you would like to train your own general model, please see our extra wiki page: How to train your own general model.
Our general models can be found and downloaded here: Download and Installation.
If you followed the installation instructions, you now have to activate the cryolo virtual environment with
source activate cryolo
You can use crYOLO either by command line or by using the GUI. The GUI should be easier for most users. You can start it with:
The crYOLO GUI is essentially a visualization of the command line interface. On left side, you find all possible “Actions”:
Each action has several parameters which are organized in tabs. Once you have chosen your settings you can press [Start] (just as example, don't press it now ), the command will be applied and crYOLO shows you the output:
It will tell you if something went wrong. Moreover, it will tell you all parameters used. Pressing [Back] brings you back to your settings, where you can either edit the settings (in case something went wrong) or go to the next action.
In the GUI choose the config action. Fill in your target box size and leave the train_image_folder and train_annot_folder fields empty.
There are three general models available. It is important that you choose the same filtering options in “Denoising options” tab as we did during training the general models. In the following are the filtering settings that we used for the respective general models:
In the configuration file, the field “anchors” is optional during prediction. That means, you don't to define a box size during prediction, as crYOLO does a size estimation internally. This is of advantage for automated pipelines. You can simply delete the entry in configuration file. This should not affect the picking quality. The estimated size is still contained in .cbox files. Coordinates in EMAN and STAR format are written with a box size of 0 in that case.
In crYOLO, all particles have an assigned confidence value. By default, all particles with a confidence value below 0.3 are discarded. If you want to pick less or more conservatively you might want to change this confidence threshold to a less (e.g. 0.2) or more (e.g. 0.4) conservative value in the “Optional arguments” tab.
However, it is much easier to select the best threshold after picking using the
CBOX files written by crYOLO as described in the next section.
When this option is activated, crYOLO will monitor your input folder. This especially useful for automation purposes. You can stop the monitor mode by writing an empty file with the name “stop.cryolo” in the input directory. Just add –monitor in the command line or check the monitor box in in the “Optional arguments” tab.
After picking is done, you can find four folders in your specified output folder:
To visualize your results you can use the boxmanager:
As image_dir you select the
full_data directory. As box_dir you select the
CBOX folder (or
EMAN_HELIX_SEGMENTED in case of filaments).
CBOX files contain besides the particle coordinates more information like the confidence and the estimated size of each particle. When importing .cbox files into the box manager, it enables more filtering options in the GUI. You can plot size- and confidence distributions. Moreover, you can change the confidence threshold, minimum and maximum size and see the results in a live preview. If you are done with the filtering, you can then write the new box selection into new box files. The video below shows an example.