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Slope.py
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import cv2 as cv
import numpy as np
import Hough as ho
import AVIC as av
def check_slope(nm_im1, nm_im2, min_gap, max_gap, lim_1, lim_2, variation, save, name, limited):
im1 = cv.imread(nm_im1)
im2 = cv.imread(nm_im2)
[img_1, matrizLinhas_1, matrizBinaria_1, variacaoMedia_1, xMedio_1, k_1, t_1,tamanhoMedio_1] = ho.HoughLinesProbabilisticoVariavel(im1,
cor = (255,0,0),
espes_linha = 1,
limiar=lim_1,
minLineGap=min_gap,
maxGap = max_gap,
cannyMinVal=75,
cannyMaxVal=150,
variacao=variation,
angulo=90,
limited=limited)
print('Processing image ' + nm_im1 + '..')
print('Average theta: ' + str(round(t_1, 5)))
[img_2, matrizLinhas_2, matrizBinaria_2, variacaoMedia_2, xMedio_2, k_2, t_2, tamanhoMedio_2] = ho.HoughLinesProbabilisticoVariavel(im2,
cor = (0,0,255),
espes_linha = 1,
limiar=lim_2,
minLineGap=min_gap,
maxGap = max_gap,
cannyMinVal=75,
cannyMaxVal=150,
variacao=variation,
angulo=90,
limited=limited)
print('\nProcessing image ' + nm_im2 + '..')
print('Average theta: ' + str(round(t_2, 5)))
print('\nvariation detected: ' + str(round(abs(t_1 - t_2), 5)))
if(save == "S"):
cv.imwrite('_result\_t1_' + name + '.jpg', img_1)
cv.imwrite('_result\_t2_' + name + '.jpg', img_2)
print("Saved")
return [img_1, img_2]
#[im1, im2] = check_slope('_base\T1_building.png', '_base\T2_building.png', 80, 80, 100, 120, 5, "S", "predio", "N")
[im1, im2] = check_slope('_base\T1_building_santos.jpg', '_base\T2_building_santos.jpg', 10, 30, 50, 50, 5, "S", "santos", "S")