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490e645ed3
* updating DIRECTORY.md
* types(maths): Fix pylance issues in maths
* reset(vsc): Reset settings changes
* Update maths/jaccard_similarity.py
Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
* revert(erosion_operation): Revert erosion_operation
* test(jaccard_similarity): Add doctest to test alternative_union
* types(newton_raphson): Add typehints to func bodies
---------
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
from pathlib import Path
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import cv2
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import numpy as np
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from matplotlib import pyplot as plt
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def get_rotation(
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img: np.ndarray, pt1: np.ndarray, pt2: np.ndarray, rows: int, cols: int
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) -> np.ndarray:
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"""
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Get image rotation
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:param img: np.ndarray
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:param pt1: 3x2 list
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:param pt2: 3x2 list
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:param rows: columns image shape
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:param cols: rows image shape
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:return: np.ndarray
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"""
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matrix = cv2.getAffineTransform(pt1, pt2)
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return cv2.warpAffine(img, matrix, (rows, cols))
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if __name__ == "__main__":
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# read original image
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image = cv2.imread(
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str(Path(__file__).resolve().parent.parent / "image_data" / "lena.jpg")
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)
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# turn image in gray scale value
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gray_img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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# get image shape
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img_rows, img_cols = gray_img.shape
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# set different points to rotate image
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pts1 = np.array([[50, 50], [200, 50], [50, 200]], np.float32)
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pts2 = np.array([[10, 100], [200, 50], [100, 250]], np.float32)
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pts3 = np.array([[50, 50], [150, 50], [120, 200]], np.float32)
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pts4 = np.array([[10, 100], [80, 50], [180, 250]], np.float32)
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# add all rotated images in a list
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images = [
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gray_img,
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get_rotation(gray_img, pts1, pts2, img_rows, img_cols),
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get_rotation(gray_img, pts2, pts3, img_rows, img_cols),
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get_rotation(gray_img, pts2, pts4, img_rows, img_cols),
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]
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# plot different image rotations
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fig = plt.figure(1)
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titles = ["Original", "Rotation 1", "Rotation 2", "Rotation 3"]
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for i, image in enumerate(images):
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plt.subplot(2, 2, i + 1), plt.imshow(image, "gray")
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plt.title(titles[i])
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plt.axis("off")
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plt.subplots_adjust(left=0.0, bottom=0.05, right=1.0, top=0.95)
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plt.show()
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