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util.py
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import cv2
import numpy as np
import imutils
from PIL import Image, ImageEnhance
from scipy.ndimage import interpolation as inter
def sharpen(img: np.ndarray, factor: float):
"""Hàm xử lý làm nét ảnh
Args:
img (numpy.ndarray): Ảnh sau khi đọc bằng opencv.
factor (float): Độ làm nét.
Returns:
enhancer (numpy.ndarray): Ảnh sau khi xử lý làm nét.
"""
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img = Image.fromarray(img)
enhancer = ImageEnhance.Sharpness(img).enhance(factor)
if gray.std() < 30:
enhancer = ImageEnhance.Contrast(enhancer).enhance(factor)
enhancer = np.array(enhancer)
return enhancer
def correct_skew(image: np.ndarray, delta=1, limit=5):
"""Hàm xử lý xoay ảnh
Args:
image (numpy.ndarray): Ảnh sau khi đọc bằng opencv.
Returns:
corrected (numpy.ndarray): Ảnh sau khi xử lý xoay.
"""
def determine_score(arr, angle):
data = inter.rotate(arr, angle, reshape=False, order=0)
histogram = np.sum(data, axis=1, dtype=float)
score = np.sum((histogram[1:] - histogram[:-1]) ** 2, dtype=float)
return histogram, score
img_new = sharpen(image, 100)
img_new = imutils.resize(img_new, height=680)
gray = cv2.cvtColor(img_new, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
scores = []
angles = np.arange(-limit, limit + delta, delta)
for angle in angles:
histogram, score = determine_score(thresh, angle)
scores.append(score)
best_angle = angles[scores.index(max(scores))]
print('best_angle ', best_angle)
if best_angle == 0:
return image
(h, w) = image.shape[:2]
center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, best_angle, 1.0)
corrected = cv2.warpAffine(image, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)
return corrected
# if __name__ == '__main__':
# # Đọc ảnh bằng opencv
# img_path = "image01.png"
# img = cv2.imread(img_path)
#
# # Gọi hàm xoay ảnh
# new_img = correct_skew(img, 2)
#
# # Hiển thị kết quả
# cv2.imshow('Before', img)
# cv2.imshow('After', new_img)
# cv2.waitKey(0)