pipeline:window:cryolo:picking_general []

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<note important>

**DOCUMENTATION OUTDATED**

The documentation has moved to https://cryolo.readthedocs.io

</note>

===== Picking particles - Without training using a general model =====
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: [[:cryolo_train_general_model|How to train your own general model]].

Our general models can be found and downloaded here: [[howto:download_latest_cryolo|Download and Installation]]. 

If you followed the installation instructions, you now have to activate the cryolo virtual environment with

<code>
source activate cryolo
</code>
==== 1. Start crYOLO ====
{{page>pipeline:window:cryolo:start_cryolo}}

==== 2. Configuration====
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.

{{ :pipeline:window:cryolo_filter_options.png?300|}} 

[[:downloads:cryolo_1#general_phosaurusnet_models|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:

  * General model trained for low-pass filtered images : Select //filter// "LOWPASS" and //low_pass_cutoff// of 0.1


  * General model trained for JANNI-denoised images: Select //filter// "JANNI" and the [[:janni_tutorial#download|janni general model]] for //janni_model//. Keep the defaults for //janni_overlap// and //janni_batches//


  * General model for negative stain images: Select filter "NONE"


<note tip>
**Anchor size is optional**

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.

</note>

<html>
<div style="background-color: #cfc ; padding: 10px; border: 1px solid green;"> 
<b>&#9658; Press the [Start] button to write the configuration file to disk.  </b>
</div>
</html>


<html>
<div style="background-color: LightCyan ; padding: 10px; border: 1px solid Black;"> 
<b>Alternative: Create the configuration file using the command line</b>
</div>
</html>

<hidden initialState="visible">
In the following I assume that you target box size is 220. Please adapt if necessary.

For the general **[[:cryolo_nets#network_3_phosaurusnet|Phosaurus network]]** trained for **low-pass filtered cryo images** run:
<code>
cryolo_gui.py config config_cryolo.json 220 --filter LOWPASS --low_pass_cutoff 0.1
</code>

For the general model trained with **neural-network denoised cryo images** (with [[:janni_tutorial#download|JANNI's general model]]) run:
<code>
cryolo_gui.py config config_cryolo.json 220 --filter JANNI --janni_model /path/to/janni_general_model.h5
</code>

For the general model for **negative stain data** please run:
<code>
cryolo_gui.py config config_cryolo.json 220 --filter NONE
</code>
</hidden>
<html>
<div style="background-color: LightCyan ; padding: 10px; border: 1px solid Black;"> 
<b> </b>
</div>
</html>
==== 3. Picking ====
{{page>pipeline:window:cryolo:picking}}

==== 4. Visualize the results ====
{{page>pipeline:window:cryolo:visualize}}
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