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cryolo_config [2018/12/20 10:35]
twagner
cryolo_config [2018/12/20 10:40]
twagner
Line 30: Line 30:
   * #12 ''batch_size'': Specified the number of images crYOLO process in parallel during training. Strongly depending on the memory of your graphic card. 6 should be fine for GPUs with 8GB memory. You can increase in case you have more memory or decrease if you have memory problems. Bigger batches tend to improve convergence and even the final error.   * #12 ''batch_size'': Specified the number of images crYOLO process in parallel during training. Strongly depending on the memory of your graphic card. 6 should be fine for GPUs with 8GB memory. You can increase in case you have more memory or decrease if you have memory problems. Bigger batches tend to improve convergence and even the final error.
  
-  * #13 ''learning_rate'':+  * #13 ''learning_rate'': Defines the step size during training. Default should be kept.
  
-  * #14 ''nb_epoch'':+  * #14 ''nb_epoch'': Maximum number of epochs the network will train. I basically never reach this number, as crYOLO stops training if it recognize that the validation loss is not improving anymore.
  
-  * #15 ''object_scale'':+  * #15 ''object_scale'': Penality scaling factor for missing picking particles.
  
-  * #16 ''no_object_scale'':+  * #16 ''no_object_scale'': Penality scaling factor for picking background.
  
-  * #17 ''coord_scale'':+  * #17 ''coord_scale'': Penality scaling factor for errors in estimating the correct position.
  
-  * #18 ''class_scale'':+  * #18 ''class_scale'': Irrelevant, as crYOLO only has the "class" "particle".
  
-  * #19 ''log_path'':+  * #19 ''log_path'': Path to folder. During training, crYOLo saves there some logs for visualization in tensorboard. Tensorboard is used to visualize curves for training and validation loss.
  
   * #20 ''saved_weights_name'':   * #20 ''saved_weights_name'':
cryolo_config.txt ยท Last modified: 2019/10/11 17:51 by twagner