STDPLearningCNN/DoG.py at main · pugilist-dev/STDPLearningCNN · GitHub

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Dec  1 09:22:38 2020

@author: rajiv
"""


import numpy as np
from skimage.filters import difference_of_gaussians
from PIL import Image


def DoG(image_name, Test= False, perceptron = False):
    train_path = "/home/rajiv/Documents/lectures/BIC/project_conv_sdnn/datasets/TrainingSet/Face/"
    test_path = "/home/rajiv/Documents/lectures/BIC/project_conv_sdnn/datasets/TestingSet/faces_labeled/"
    perceptron_path = "/home/rajiv/Documents/lectures/BIC/project_conv_sdnn/datasets/TrainingSet/faces_labeled/"
    if Test:
        image = Image.open(test_path + image_name)
        image = np.array(image.resize((400,400), Image.BILINEAR))
        filtered_image = difference_of_gaussians(image, 1.5)
        filtered_image = np.expand_dims(filtered_image, axis = 0)
        filtered_image = np.expand_dims(filtered_image, axis = 0)
        return filtered_image
    elif perceptron:
        image = Image.open(perceptron_path + image_name)
        image = np.array(image.resize((400,400), Image.BILINEAR))
        filtered_image = difference_of_gaussians(image, 1.5)
        filtered_image = np.expand_dims(filtered_image, axis = 0)
        filtered_image = np.expand_dims(filtered_image, axis = 0)
        return filtered_image
    else:
        image = Image.open(train_path+image_name)
        image = np.array(image.resize((400,400), Image.BILINEAR))
        filtered_image = difference_of_gaussians(image, 1.5)
        filtered_image = np.expand_dims(filtered_image, axis = 0)
        filtered_image = np.expand_dims(filtered_image, axis = 0)
        return filtered_image