pythonopencvhoughlinesp

Opencv python HoughLinesP strange results

I'm trying to get the same result they got in this tutorial for HoughLinesP filter. I took same images and same threshold values like this : 

import cv2
from line import Line
import numpy as np

img = cv2.imread('building.jpg',1)
cannied = cv2.Canny(img, 50, 200, 3)
lines = cv2.HoughLinesP(cannied, 1, np.pi / 180, 80, 30, 10)


for leftx, boty, rightx, topy in lines[0]:
    line = Line((leftx, boty), (rightx,topy))
    line.draw(img, (255, 255, 0), 2)

cv2.imwrite('lines.png',img)
cv2.imwrite('canniedHouse.png',cannied)
cv2.waitKey(0)
cv2.destroyAllWindows()

Line class is a custom class that does not do anything interesting just calculates some stuff and can draw the line. And then I get these two images : enter image description here enter image description here

So as you can see I get only one litle line in the midle of the image.

Not sure what's going wrong. Did I miss some thing?

Thanks.

Solution

  • NOTE: Since you linked a tutorial for OpenCV 2.4.x, I initially assumed you also wrote your code with OpenCV 2.4.11. As it turns out, you're actually using OpenCV 3.x. Keep in mind that there are subtle changes in the API between 2.x and 3.x.

    You call HoughLinesP incorrectly.

    According to the documentation, the signature of the Python function is:

    cv2.HoughLinesP(image, rho, theta, threshold[, lines[, minLineLength[, maxLineGap]]]) → lines

    If we label the parameters in your call, we get the following:

    lines = cv2.HoughLinesP(cannied, rho=1, theta=np.pi / 180
    , threshold=80, lines=30, minLineLength=10)

    However, the C++ code correctly ported to Python would be

    lines = cv2.HoughLinesP(cannied, rho=1, theta=np.pi / 180
    , threshold=80, minLineLength=30, maxLineGap=10)

    Result

    Similar situation with Canny

    cv2.Canny(image, threshold1, threshold2[, edges[, apertureSize[, L2gradient]]]) → edges

    Again, let's label the parameters:

    cannied = cv2.Canny(img, threshold1=50, threshold2=200, edges=3)

    But it should be:

    cannied = cv2.Canny(img, threshold1=50, threshold2=200, apertureSize=3)

    However this makes no difference in the output, since the default value for apertureSize is 3.

    Finally, as we identified with Vasanth and namatoj, there is a difference in the format of the output generated by cv2.HoughLinesP:

    I added a short get_lines function to transform the lines into consistent layout ([[x1, y1, x2, y2], [...], ..., [...]]) in both versions.

    Full script that works in both OpenCV versions:

    import cv2
import numpy as np


def get_lines(lines_in):
    if cv2.__version__ < '3.0':
        return lines_in[0]
    return [l[0] for l in lines]


img = cv2.imread('building.jpg')
img_gray = gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

cannied = cv2.Canny(img_gray, threshold1=50, threshold2=200, apertureSize=3)
lines = cv2.HoughLinesP(cannied, rho=1, theta=np.pi / 180, threshold=80, minLineLength=30, maxLineGap=10)

for line in get_lines(lines):
    leftx, boty, rightx, topy = line
    cv2.line(img, (leftx, boty), (rightx,topy), (255, 255, 0), 2)

cv2.imwrite('lines.png',img)
cv2.imwrite('canniedHouse.png',cannied)
cv2.waitKey(0)
cv2.destroyAllWindows()