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pipeline:window:cryolo:picking_general [2019/10/11 17:11]
twagner [2. Configuration] 		pipeline:window:cryolo:picking_general [2020/06/05 09:03] (current)
twagner
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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 +**DOCUMENTATION OUTDATED**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 ===== ===== 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]].
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   * General model for negative stain images: Select filter "NONE"   * 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> <html>
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 For the general **[[:cryolo_nets#network_3_phosaurusnet|Phosaurus network]]** trained for **low-pass filtered cryo images** run: For the general **[[:cryolo_nets#network_3_phosaurusnet|Phosaurus network]]** trained for **low-pass filtered cryo images** run:
 <code> <code>
-cryolo_gui.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> </code>
  
 For the general model trained with **neural-network denoised cryo images** (with [[:janni_tutorial#download|JANNI's general model]]) run: For the general model trained with **neural-network denoised cryo images** (with [[:janni_tutorial#download|JANNI's general model]]) run:
 <code> <code>
-cryolo_gui.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> </code>
  
 For the general model for **negative stain data** please run: For the general model for **negative stain data** please run:
 <code> <code>
-cryolo_gui.py config config_cryolo_.json 220 --filter NONE+cryolo_gui.py config config_cryolo.json 220 --filter NONE
 </code> </code>
 </hidden> </hidden>
pipeline/window/cryolo/picking_general.1570806669.txt.gz ยท Last modified: 2019/10/11 17:11 by twagner

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