Resolved: How do you detect the largest set of parallel lines in an image?

import cv2
import numpy as np
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt


img = cv2.imread('UI5Mr.png')


gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)


edges = cv2.Canny(gray, 50, 150, apertureSize=3)


lines = cv2.HoughLinesP(edges, rho=1, theta=np.pi/180, threshold=100, minLineLength=100, maxLineGap=10)


X = np.array([[x1, y1, x2, y2] for [[x1, y1, x2, y2]] in lines])
kmeans = KMeans(n_clusters=2)
kmeans.fit(X[:, [2, 3]] - X[:, [0, 1]])
labels = kmeans.labels_
centers = kmeans.cluster_centers_


counts = np.bincount(labels)
largest_cluster_idx = np.argmax(counts)
largest_cluster_mask = (labels == largest_cluster_idx)
largest_cluster_lines = X[largest_cluster_mask]


for [x1, y1, x2, y2] in largest_cluster_lines:
    cv2.line(img, (x1, y1), (x2, y2), (0, 255, 0), 2)


plt.imshow(img)