utils.py

import cv2
import numpy as np

def read_img(input_path) :
    img = cv2.cvtColor(cv2.imread(input_path), cv2.COLOR_BGR2RGB)
    return img

def edge_detection(img, line_wdt, blur):
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    grayBlur = cv2.medianBlur(gray,blur)
    edges = cv2.adaptiveThreshold(grayBlur, 255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,line_wdt,blur)
    return edges

def color_quantisation(img, k):
    data = np.float32(img).reshape((-1,3))
    criteria = (cv2.TermCriteria_EPS + cv2.TERM_CRITERIA_MAX_ITER,20,0.001)
    ret, label, center = cv2.kmeans(data,k,None,criteria,10,cv2.KMEANS_RANDOM_CENTERS)
    center = np.uint8(center)
    result = center[label.flatten()]
    result=result.reshape(img.shape)
    return result