import cv2
import numpy as np
from os.path import getsize
from IPython.display import Markdown as md
from matplotlib import pyplot as plt
from skimage.exposure import rescale_intensity

name = "stitch.jpg"
image = cv2.imread(name,cv2.IMREAD_GRAYSCALE)
height, width = image.shape

image_sobel=np.zeros(image.shape, dtype="float32")

sobelx = np.array(
    [[-1,-2,-1],
     [0,0,0],
     [1,2,1]])
sobely = np.array(
    [[-1,0,1],
     [-2,0,2],
     [-1,0,1]])

for h in range(height-2):
    for w in range(width-2):
        a = np.float32(image[h:h+3,w:w+3]) # submatriz 3x3 ao redor do pixel image[h+1,w+1]
        dx=np.sum(np.multiply(a,sobelx)) # derivada sobel em relacao a x
        dy=np.sum(np.multiply(a,sobely)) # derivada sobel em relacao a y
        image_sobel[h+1][w+1]=np.sqrt(np.power(dx,2) + np.power(dy,2))

# normalizando intensidades dos pixels para dentro do range [0,255]
# https://www.pyimagesearch.com/2016/07/25/convolutions-with-opencv-and-python/
image_sobel = rescale_intensity(image_sobel, in_range=(0, 255))
image_sobel = (image_sobel * 255).astype("uint8")

image_roberts=np.zeros(image.shape, dtype="float32")

robertsx = np.array(
    [[1,0],
     [0,-1]])
robertsy = np.array(
    [[-1,0],
     [0,1]])

for h in range(height-1):
    for w in range(width-1):
        a = np.float32(image[h:h+2,w:w+2]) # submatriz 2x2 ao redor do pixel image[h+1,w+1]
        dx=np.sum(np.multiply(a,robertsx))
        dy=np.sum(np.multiply(a,robertsy))
        image_roberts[h+1][w+1]=np.sqrt(np.power(dx,2) + np.power(dy,2))

# normalizando intensidades dos pixels para dentro do range [0,255]
image_roberts = rescale_intensity(image_roberts, in_range=(0, 255))
image_roberts = (image_roberts * 255).astype("uint8")

fig=plt.figure(figsize=(25,25))
fig.add_subplot(1,3,1)
plt.title("Imagem original cinza")
plt.imshow(image,cmap="gray")
plt.xticks([]),plt.yticks([])
fig.add_subplot(1,3,2)
plt.title("Resultado do filtro Sobel")
plt.imshow(image_sobel,cmap="gray")
plt.xticks([]),plt.yticks([])
fig.add_subplot(1,3,3)
plt.title("Resultado do filtro Roberts")
plt.imshow(image_roberts,cmap="gray")
plt.xticks([]),plt.yticks([])
plt.show()

cv2.imshow("Imagem original cinza",image)
cv2.imshow("Resultado do filtro Sobel",image_sobel)
cv2.imshow("Resultado do filtro Roberts",image_roberts)
cv2.waitKey(0)
cv2.destroyAllWindows()