Draws a line and hows Hough Space

hough_lines

import cv2, numpy as np, math

# Parameters
num_dots, hw, num_bins = 10, 400, 400
# Read image that has two lines in it
lines = np.zeros((hw,hw), np.uint8)

# Create a row of diagonal dots
space = int(hw / (num_dots+1))
for i in range(num_dots): cv2.circle(lines, (space*(i+1), space*(i+1)), 0, 255, 1)

# Create accumulator array
accumulator = np.zeros((num_bins,num_bins), np.uint8)

# Calculate the diagonal distance of the image (used to scale rho)
diag = math.sqrt(lines.shape[0]**2 + lines.shape[1]**2)

# Iterate through each row in the image
for x in range(lines.shape[0]):
    # Iterate through each column in the image
    for y in range(lines.shape[1]):
        # Get the pixel value for this row, column
        px = lines[x, y]
        # If the pixel value is not black
        if px != 0:
            # Iterate through theta values
            for theta_idx in range(num_bins):
                # Calculate theta
                theta = theta_idx * math.pi / num_bins                
                # Calculate rho
                rho = x * math.cos(theta) + y * math.sin(theta)                
                # Scale rho so that it is a value between 0 and num_bins
                rho = int(num_bins * .5 * (rho+diag) / diag)
                # Increment the appropriate bin
                accumulator[rho, theta_idx] += 1

# Make a circle around the brightest spot
_, _, _, maxLoc = cv2.minMaxLoc(accumulator)
cv2.circle(accumulator, maxLoc, 25, 255, 2)

# Threshold the accumulator (this makes the lines visible)
_, accumulator = cv2.threshold(accumulator, 0, 255, 0)

# Show image
cv2.imshow('img', cv2.dilate(lines,np.ones((5,5),np.uint8),iterations = 2))
cv2.imshow('accumulator', cv2.resize(accumulator, (hw,hw)))
cv2.imwrite('/home/stephen/Desktop/lines.png', cv2.dilate(lines,np.ones((5,5),np.uint8),iterations = 2))
cv2.imwrite('/home/stephen/Desktop/accumulator.png', cv2.resize(accumulator, (hw,hw)))
cv2.waitKey(0)
cv2.destroyAllWindows()