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--- pipeline:window:cryolo:picking [2019/09/14 10:14]
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+++ pipeline:window:cryolo:picking [2019/09/17 08:17]
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@@ Line 1: / Line 1: @@
-You can now use the model weights file (//e.g. ''model.h5'' in training from scratch or ''gmodel_phosnet_X_Y.h5'' when using the general model//) to pick all your images in the directory ''full_data''. To do this, run:
+Select the actin prediction and fill all arguments in the //"Required arguments"// tab:
+{{ :pipeline:window:cryolo:cryolo_prediction.png?600 |}}
+<note tip>
+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 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>
+<hidden **Run prediction from the command line**>
+You can now use the model weights file (//e.g. ''cryolo_model.h5'' in training from scratch or ''gmodel_phosnet_X_Y.h5'' when using the general model//) to pick all your images in the directory ''full_data''. To do this, run:
 <code>
-cryolo_predict.py -c config.json -w model.h5 -i full_data/ -g 0 -o boxfiles/
+cryolo_predict.py -c config.json -w cryolo_model.h5 -i full_data/ -g 0 -o boxfiles/
 </code>
 You will find the picked particles in the directory ''boxfiles''.
-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:
-<code>
+</hidden>
-cryolo_predict.py -c config.json -w model.h5 -i full_data/ -g 0 -o boxfiles/ -t 0.2
-</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

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