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--- pipeline:window:cryolo:picking_general [2019/09/17 14:15]
twagner [Picking particles - Without training using a general model]
+++ pipeline:window:cryolo:picking_general [2020/06/05 09:03]
twagner
@@ Line 1: / Line 1: @@
+<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+**DOCUMENTATION OUTDATED**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]]
+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]].
@@ Line 9: / Line 17: @@
 source activate cryolo
 </code>
-==== Start crYOLO ====
+==== 1. Start crYOLO ====
 {{page>pipeline:window:cryolo:start_cryolo}}
-==== Configuration====
+==== 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 //"Model/denoising options"// tab as we did during training the general models:
+[[: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>Press the Start button to write the configuration file to disk.  </b>
+<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 **Create the configuration file using the command line**>
+<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>
-cryoloo.py config config_cryolo_.json 220 --filter LOWPASS --low_pass_cutoff 0.1
+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>
-cryoloo.py config config_cryolo_.json 220 --filter JANNI --janni_model /path/to/janni_general_model.h5
+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>
-cryoloo.py config config_cryolo_.json 220 --filter NONE
+cryolo_gui.py config config_cryolo.json 220 --filter NONE
 </code>
 </hidden>
+<html>
-==== Picking ====
+<div style="background-color: LightCyan ; padding: 10px; border: 1px solid Black;">
+<b> </b>
+</div>
+</html>
+==== 3. Picking ====
 {{page>pipeline:window:cryolo:picking}}
-==== Visualize the results ====
+==== 4. Visualize the results ====
 {{page>pipeline:window:cryolo:visualize}}

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