Open Source Computer Vision Library https://opencv.org/
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'''
Text skewness correction
This tutorial demonstrates how to correct the skewness in a text.
The program takes as input a skewed source image and shows non skewed text.
Usage:
python text_skewness_correction.py --image "Image path"
'''
import numpy as np
import cv2 as cv
import sys
import argparse
def main():
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--image", required=True, help="path to input image file")
args = vars(parser.parse_args())
# load the image from disk
image = cv.imread(cv.samples.findFile(args["image"]))
if image is None:
print("can't read image " + args["image"])
sys.exit(-1)
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
# threshold the image, setting all foreground pixels to
# 255 and all background pixels to 0
thresh = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)[1]
# Applying erode filter to remove random noise
erosion_size = 1
element = cv.getStructuringElement(cv.MORPH_RECT, (2 * erosion_size + 1, 2 * erosion_size + 1), (erosion_size, erosion_size) )
thresh = cv.erode(thresh, element)
coords = cv.findNonZero(thresh)
angle = cv.minAreaRect(coords)[-1]
# the `cv.minAreaRect` function returns values in the
# range [-90, 0) if the angle is less than -45 we need to add 90 to it
if angle < -45:
angle = (90 + angle)
(h, w) = image.shape[:2]
center = (w // 2, h // 2)
M = cv.getRotationMatrix2D(center, angle, 1.0)
rotated = cv.warpAffine(image, M, (w, h), flags=cv.INTER_CUBIC, borderMode=cv.BORDER_REPLICATE)
cv.putText(rotated, "Angle: {:.2f} degrees".format(angle), (10, 30), cv.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
# show the output image
print("[INFO] angle: {:.2f}".format(angle))
cv.imshow("Input", image)
cv.imshow("Rotated", rotated)
cv.waitKey(0)
if __name__ == "__main__":
main()