laplacian.py

from skimage.exposure import rescale_intensity
import numpy as np
import argparse
import cv2

def convolve(image, kernel):
	(iH, iW) = image.shape[:2]
	(kH, kW) = kernel.shape[:2]
	pad = (kW - 1) // 2
	image = cv2.copyMakeBorder(image, pad, pad, pad, pad,
		cv2.BORDER_REPLICATE)
	output = np.zeros((iH, iW), dtype="float32")
	for y in np.arange(pad, iH + pad):
		for x in np.arange(pad, iW + pad):
			roi = image[y - pad:y + pad + 1, x - pad:x + pad + 1]
			k = (roi * kernel).sum()
			output[y - pad, x - pad] = k

	output = rescale_intensity(output, in_range=(0, 255))
	output = (output * 255).astype("uint8")
	return output

ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
	help="path to the input image")
args = vars(ap.parse_args())

laplacian = np.array((
	[0, 1, 0],
	[1, -4, 1],
	[0, 1, 0]), dtype="int")


kernelBank = (
	("laplacian", laplacian),
)


image = cv2.imread(args["image"])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.imwrite("original.jpg",gray)

for (kernelName, kernel) in kernelBank:
	print("[INFO] applying {} kernel".format(kernelName))
	convoleOutput = convolve(gray, kernel)
	opencvOutput = cv2.filter2D(gray, -1, kernel)
	cv2.imshow("original", gray)
	cv2.imshow("{} - convole".format(kernelName), convoleOutput)
	cv2.imshow("{} - opencv".format(kernelName), opencvOutput)
	cv2.imwrite("laplacian.jpg", convoleOutput)
	cv2.waitKey(0)
	cv2.destroyAllWindows()