class_utils.py

# This is for ECE580: Intro to machine learning Spring 2020 in Duke
# This is translated to Python from show_chanWeights.m file provided by Prof. Li by 580 TAs

# import ext libs
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# from scipy.misc import imread   # Make Sure you install the required packages like Pillow and scipy

def imgRead(fileName):
    """
    load the input image into a matrix
    :param fileName: name of the input file
    :return: a matrix of the input image
    Examples: imgIn = imgRead('lena.bmp')
    """
    imgIn = plt.imread(fileName)
    return imgIn


def imgShow(imgOut,title='Default Title'):
    """
    show the image saved in a matrix
    :param imgOut: a matrix containing the image to show
    :return: None
    """
    imgOut = np.uint8(imgOut)
    plt.imshow(imgOut)
    plt.title(title)
    plt.show()

def imgSave(savedir,filename,filename_extension,img=[],cmap='gray',vmin=0,vmax=255):
    img = np.uint8(img)
    index = filename.find('.') # cut off the 
    plt.imsave(savedir + '/' +filename[:index] + '_' + filename_extension + '.png',img)

def imgRecover(imgIn, blkSize, numSample):
    """
    Recover the input image from a small size samples
    :param imgIn: input image
    :param blkSize: block size
    :param numSample: how many samples in each block
    :return: recovered image
    """
    ##### Your Implementation here

    return None

"""
if __name__ == '__main__':
    a = imgRead('lena.bmp')
    print(np.shape(a))
    imgShow(a)
    print(a)
"""