ali-john

import numpy as np
import cv2 as opencv

# Read Image
image = opencv.imread('einstein.PNG', opencv.IMREAD_GRAYSCALE)
fifth_percentile = np.percentile(image, 5)  # 5th percentile- used as min value 
nintyfive_percentile = np.percentile(image, 95)  # used for max value
output = np.zeros([image.shape[0], image.shape[1]], dtype=np.uint8)
# pixel value less than 5th percentile -- set to 0
# pixel value > 95th percentile -- set to 255

ali-john

import numpy as np
import cv2 as opencv
import Transforms
import od as o
import cca
import pad as p
import csv
import os

ali-john

def maxFilter(img, size):
    out = np.zeros([img.shape[0], img.shape[1]], dtype="int")
    for i in range(img.shape[0] - size):
        for j in range(img.shape[1] - size):
            mat = img[i: i + size, j: j + size]
            mat = np.ravel(mat)  # convert to 1D array
            mat = np.sort(mat)
            out[i, j] = np.max(mat)
    return out

ali-john

import numpy as np
import cv2 as opencv
import random as r


def neighbours(i, j, src):
    # left
    left = src[i, j - 1]
    # top
    top = src[i - 1, j]