How to use the output of cv2.HoughLinesP() to rotate the original image?

Question

I'm using cv2.HoughLinesP() and it's giving me lines it has detected. These lines are mostly accurate at finding the angle of the object. Then, I want to rotate the original image according to these lines.

My image:

My code:

import cv2 as cv
import numpy as np
img = cv.imread(img)
gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
edges = cv.Canny(gray,50,150,apertureSize = 3)
lines = cv.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)
for line in lines:
    x1,y1,x2,y2 = line[0]
    cv.line(img,(x1,y1),(x2,y2),(0,255,0),5)
cv2.imshow('', img)
cv2.waitKey()

The result:

What I want:

Answer 1

It seems you're trying to perform skew correction. Instead of using cv2.HoughLinesP to find the angle and rotate the object, you can use cv2.minAreaRect to find the angle then cv2.getRotationMatrix2D + cv2.warpAffine to deskew the image.

Input -> Output

Skew angle

-29.35775375366211

Code

import cv2
import numpy as np

# Load image, grayscale, Otsu's threshold 
image = cv2.imread('1.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = 255 - gray
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# Compute rotated bounding box
coords = np.column_stack(np.where(thresh > 0))
angle = cv2.minAreaRect(coords)[-1]

if angle < -45:
    angle = -(90 + angle)
else:
    angle = -angle
print(angle)

# Rotate image to deskew
(h, w) = image.shape[:2]
center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, angle, 1.0)
rotated = cv2.warpAffine(image, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)

cv2.imshow('thresh', thresh)
cv2.imshow('rotated', rotated)
cv2.waitKey()

Note: For other skew correction techniques take a look at

1. Python OpenCV skew correction

2. How to de-skew an image

3. Detect image orientation angle based on text direction