orcanet_contrib.parser_orcapred
Use orga.predict with a parser.
- Usage:
parser_orcapred.py FOLDER LIST CONFIG MODEL [–epoch EPOCH] [–fileno FILENO] parser_orcapred.py (-h | –help)
- Arguments:
- FOLDER Path to the folder where everything gets saved to, e.g. the
summary.txt, the plots, the trained models, etc.
- LIST A .toml file which contains the pathes of the training and
validation files. An example can be found in examples/list_file.toml
- CONFIG A .toml file which sets up the training. An example can be
found in examples/config_file.toml. The possible parameters are listed in core.py in the class Configuration.
- MODEL Path to a .toml file with infos about a model.
An example can be found in examples/explanation.toml.
- Options:
-h –help Show this screen. –epoch=EPOCH Use model of given epoch. [default: None] –fileno=FILENO Use model of given fileno. [default: None]
Module Contents
Functions
|
Run orga.predict with predefined ModelBuilder networks using a parser. |
|
Run the orca_pred function with a parser. |
- orcanet_contrib.parser_orcapred.orca_pred(output_folder, list_file, config_file, model_file, epoch=None, fileno=None)[source]
Run orga.predict with predefined ModelBuilder networks using a parser.
Per default, the most recent saved model will be loaded.
- Parameters
- output_folderstr
Path to the folder where everything gets saved to, e.g. the summary log file, the plots, the trained models, etc.
- list_filestr
Path to a list file which contains pathes to all the h5 files that should be used for training and validation.
- config_filestr
Path to a .toml file which overwrites some of the default settings for training and validating a model.
- model_filestr
Path to a file with parameters to build a model of a predefined architecture with OrcaNet.
- epochint, optional
The epoch of the saved model to predict with.
- filenoint, optional
The filenumber of the saved model to predict with.