############################################################################################

#

# Project:       Peter Moss Acute Myeloid & Lymphoblastic Leukemia AI Research Project

# Repository:    ALL Detection System 2019

# Project:       Data Augmentation

#

# Author:        Adam Milton-Barker (AdamMiltonBarker.com)

# Contributors:

# Title:         Manual Data Augmentation Class

# Description:   Manual data augmentation class for the ALL Detection System 2019.

# License:       MIT License

# Last Modified: 2020-07-14

#

############################################################################################

import matplotlib.pyplot as plt

from Classes.Data import Data

plt.rcParams['figure.figsize'] = (5.0, 4.0)

plt.rcParams['image.interpolation'] = 'nearest'

plt.rcParams['image.cmap'] = 'gray'

class Augmentation():

    """ ALL Detection System 2019 Manual Data Augmentation Class

    Manual data augmentation wrapper class for the ALL Detection System 2019 Data Augmentation project.

    """

    def __init__(self):

        """ Initializes the Augmentation class. """

        self.Data = Data()

    def processDataset(self):

        """ Processes the AML/ALL Detection System Dataset. 

        Make sure you have your equal amounts of positive and negative

        samples in the Model/Data directories.

        Only run this function once! it will continually make copies

        of all images in the Settings->TrainDir directory specified

        in Required/confs.json

        """

        self.Data.processDataset()

print("!! Data Augmentation Program Starting !!")

print("")

Augmentation = Augmentation()

Augmentation.processDataset()

print(" Data Augmentation Program Complete")

print("")