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--- pipeline:window:cryolo:picking [2019/09/14 10:12]
twagner created
+++ pipeline:window:cryolo:picking [2019/09/17 15:01]
twagner
@@ Line 1: / Line 1: @@
-You can now use the model weights saved in ''model.h5'' (//if you come to this section from another point of the tutorial, this filename might be different like ''gmodel_phosnet_X_Y.h5''//) to pick all your images in the directory ''full_data''. To do this, run:
+Select the action "predict" and fill all arguments in the //"Required arguments"// tab:
-<code>
+{{ :pipeline:window:cryolo:cryolo_prediction.png?600 |}}
-cryolo_predict.py -c config.json -w model.h5 -i full_data/ -g 0 -o boxfiles/
-</code>
-You will find the picked particles in the directory ''boxfiles''.
+<note tip>
+In crYOLO, all particles have a assigned confidence value. By default, all particle with confidence value below 0.3 are discarded. If you want to pick less conservatively or more conservatively you might want to change this confidence threshold to a less conservative value like 0.2 or more conservative value like 0.4 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.
+</note>
-If you want to pick less conservatively or more conservatively you might want to change the selection threshold from the default of 0.3 to a less conservative value like 0.2 or more conservative value like 0.4 using the //-t// parameter:
+<html>
+<div style="background-color: #cfc ; padding: 10px; border: 1px solid green;">
+<b>Press the the Start button to run the prediction.  </b>
+</div>
+</html>
+You will find the picked particles in your specified output directory.
+<hidden **Run prediction from the command line**>
+To pick all your images in the directory ''full_data'' with the  model weights file ''cryolo_model.h5'' (//e.g. or ''gmodel_phosnet_X_Y.h5'' when using the general model//) and and a confidence threshold of 0.3 run::
 <code>
-cryolo_predict.py -c config.json -w model.h5 -i full_data/ -g 0 -o boxfiles/ -t 0.2
+cryolo_predict.py -c config.json -w cryolo_model.h5 -i full_data/ -g 0 -o boxfiles/ -t 0.3
 </code>
-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
+You will find the picked particles in the directory ''boxfiles''.
+</hidden>

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