diff options
Diffstat (limited to 'ricky/dataset.py')
| -rw-r--r-- | ricky/dataset.py | 32 |
1 files changed, 6 insertions, 26 deletions
diff --git a/ricky/dataset.py b/ricky/dataset.py index 4f8a422..478ee5e 100644 --- a/ricky/dataset.py +++ b/ricky/dataset.py @@ -3,24 +3,6 @@ from ricky.utils import data_from_image from pybrain.datasets import SupervisedDataSet -# while subclassing this works, we should try to detect the length of params -# and build a new data set for each type of params set... -# therefore, an instance of SupervisedDataSet could actually be -# accessed through the params instance...simplified one-to-one mapping - -# we are limited to only one classifier per params instance as well -# however this is sort of a good thing, because built into the params -# class can be a method that randomizes params, and then evaluates - -# we might be able to get this done through multiple inheritance -# keep all dataset related stuff in a separate class to make it better organized - -# we need -# .evaluate -# .generate_liked_image -# .train_from_url_list -# .reset - class DataSet(SupervisedDataSet): @@ -35,11 +17,9 @@ class DataSet(SupervisedDataSet): target = 1 data_list = [data_from_image(image) for image in url_list if image] for data in data_list: - for params_class in ricky.params.Params.__subclasses__(): - if data['module'] == params_class.__name__: - params_instance = params_class() - params_instance.from_dict(data['params']) - self.addSample( - params_instance.as_normalized(), - target - ) + params_instance = Params.new_class_from_classname(data['module']) + params_instance.from_dict(data['params']) + self.addSample( + params_instance.as_normalized(), + target + ) |