Create utils.py

utils.py

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+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