本文实例为大家分享了opencv实现图像校正的具体代码,供大家参考,具体内容如下
1.引言:python实现倾斜图像校正操作
2.思路流程:
(1)读入,灰度化;
(2)高斯模糊;
(3)二值化图像;
(4)闭开操作;
(5)获取图像顶点;
(6)旋转校正
3.实现代码:
import cv2 import numpy as np import imutils import time def img_outline(img_path): original_img = cv2.imread(img_path) gray_img = cv2.cvtcolor(original_img, cv2.color_bgr2gray) blurred = cv2.gaussianblur(gray_img, (9, 9), 0) # 高斯模糊去噪(设定卷积核大小影响效果) _, redthresh = cv2.threshold(blurred, 165, 255, cv2.thresh_binary) # 设定阈值165(阈值影响开闭运算效果) kernel = cv2.getstructuringelement(cv2.morph_rect, (5, 5)) # 定义矩形结构元素 closed = cv2.morphologyex(redthresh, cv2.morph_close, kernel) # 闭运算(链接块) opened = cv2.morphologyex(closed, cv2.morph_open, kernel) # 开运算(去噪点) return original_img, opened def findcontours_img(original_img, opened): contours = cv2.findcontours(opened, cv2.retr_list, cv2.chain_approx_simple) cnts = imutils.grab_contours(contours) # print(cnts) # c = sorted(cnts, key=cv2.contourarea, reverse=true)[0] # 计算最大轮廓的旋转包围盒 c = max(cnts, key=cv2.contourarea) rect = cv2.minarearect(c) # print(rect) angle = rect[2] # rect[2] 返回的是矩形的旋转角度 print("angle", angle) if angle == 90.0: return original_img, original_img else: box = np.int0(cv2.boxpoints(rect)) draw_img = cv2.drawcontours(original_img.copy(), [box], -1, (0, 0, 255), 3) rows, cols = original_img.shape[:2] m = cv2.getrotationmatrix2d((cols / 2, rows / 2), angle, 1) result_img = cv2.warpaffine(original_img, m, (cols, rows)) return result_img,draw_img if __name__ == "__main__": img_path = './result.jpg' start_time = time.time() original_img, opened = img_outline(img_path) result_img,draw_img = findcontours_img(original_img,opened) print('消耗的时间为:',(time.time() - start_time)) cv2.imshow("original_img", original_img) cv2.imshow("draw_img", draw_img) cv2.imshow("result_img", result_img) cv2.waitkey(0) cv2.destroyallwindows()
4.效果展示:
原图
标框出图
旋转后的图
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持。