datahandler.py
def import_training_data(self, data_path):
        """Import the training data from a given input path. Assuming that
        the input path only contains folders where the folder name designates
        the image label. All sub-directories are searched but their names are
        ignored.
        """
        folders = os.listdir(data_path)
        training_set = {}

        for folder in folders:
            folder_path = os.path.join(data_path, folder)
            if os.path.isdir(folder_path):
                new_images = self.search_folder_for_images(folder_path)
                folder_name = folder.split('/')[-1]
                training_set[folder_name] = new_images

        print('Training data set imported.')
        return training_set
Import the training data from a given input path. Assuming that
        the input path only contains folders where the folder name designates
        the image label. All sub-directories are searched but their names are
        ignored.
        
Import the training data from a given input path. Assuming that
the input path only contains folders where the folder name designates
the image label. All sub-directories are searched but their names are
ignored.
Import the training data from a given input path . Assuming that the input path only contains folders where the folder name designates the image label . All sub - directories are searched but their names are ignored .
def import_training_data(self, data_path):
        folders = os.listdir(data_path)
        training_set = {}
        for folder in folders:
            folder_path = os.path.join(data_path, folder)
            if os.path.isdir(folder_path):
                new_images = self.search_folder_for_images(folder_path)
                folder_name = folder.split('/')[-1]
                training_set[folder_name] = new_images
        print('Training data set imported.')
        return training_set
def import_training_data ( self , data_path ) : folders = os . listdir ( data_path ) training_set = { } for folder in folders : folder_path = os . path . join ( data_path , folder ) if os . path . isdir ( folder_path ) : new_images = self . search_folder_for_images ( folder_path ) folder_name = folder . split ( '/' ) [ - 1 ] training_set [ folder_name ] = new_images print ( 'Training data set imported.' ) return training_set
Import the training data from a given input path.
Import the training data from a given input path .
"""Import the training data from a given input path. Assuming that
        the input path only contains folders where the folder name designates
        the image label. All sub-directories are searched but their names are
        ignored.
        """
self
data_path