Hough space for cv2 houghlines - opencv

Question

I am having some trouble with cv2.Houghlines() showing vertical lines when I believe that the real fit should provide horizontal lines.
Here is a clip of the code I am using:
rho_resoultion = 1
theta_resolution = np.pi/180
threshold = 200
lines = cv2.HoughLines(image, rho_resoultion, theta_resolution, threshold)
# print(lines)
for line in lines:
rho, theta = line[0]
a = np.cos(theta)
b = np.sin(theta)
x0 = a*rho
y0 = b*rho
x1 = int(x0 + 1000*(-b))
y1 = int(y0 + 1000*(a))
x2 = int(x0 - 1000*(-b))
y2 = int(y0 - 1000*(a))
cv2.line(image,(x1,y1),(x2,y2),(255,255,255),1)
cv2.namedWindow('thing', cv2.WINDOW_NORMAL)
cv2.imshow("thing", image)
cv2.waitKey(0)
This is the input and output:
I think it would be easier to extract out what is occurring if the Hough space image could be viewed.
However, the documentation does not provide information for how to show the full hough space.
How would one show the whole Hough transform space?
I attempted reducing the threshold to 1 but it did not provide an image.

Answer 1

Maybe you got something wrong when calculationg the angles. Feel free to show some code.
Here is an example of how to show all Hough lines in an image:
import cv2
import numpy as np
img = cv2.imread('sudoku.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
lines = cv2.HoughLines(edges,1,np.pi/180,200)
for line in lines:
for rho,theta in line:
a = np.cos(theta)
b = np.sin(theta)
x0 = a*rho
y0 = b*rho
x1 = int(x0 + 1000*(-b))
y1 = int(y0 + 1000*(a))
x2 = int(x0 - 1000*(-b))
y2 = int(y0 - 1000*(a))
cv2.line(img,(x1,y1),(x2,y2),(0,0,255),2)
cv2.imshow('Houghlines',img)
if cv2.waitKey(0) & 0xff == 27:
cv2.destroyAllWindows()
Original image:
Result: