python opencv实现图片旋转矩形分割_Python

有时候需要对有角度的矩形框内图像从原图片中分割出来。这里的程序思想是，先将图片进行矩形角度的旋转，使有角度的矩形处于水平状态后，根据原来坐标分割图片。
参考：python opencv实现旋转矩形框裁减功能

修改原来的程序：

1.旋转函数的输入仅为矩形的四点坐标
2.角度由公式计算出来
3.矩形四点pt1,pt2,pt3,pt4由txt文件读入
4.在旋转程序中还处理了顺时针和逆时针及出现矩形框翻转的问题。

代码：

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									# -*- coding:utf-8 -*-

									import cv2

									from math import *

									import numpy as np

									import time,math

									import os

									import re

									'''旋转图像并剪裁'''

									def rotate(

									    img, # 图片

									    pt1, pt2, pt3, pt4

									):

									  print pt1,pt2,pt3,pt4

									  withrect = math.sqrt((pt4[0] - pt1[0]) ** 2 + (pt4[1] - pt1[1]) ** 2) # 矩形框的宽度

									  heightrect = math.sqrt((pt1[0] - pt2[0]) ** 2 + (pt1[1] - pt2[1]) **2)

									  print withrect,heightrect

									  angle = acos((pt4[0] - pt1[0]) / withrect) * (180 / math.pi) # 矩形框旋转角度

									  print angle

									  if pt4[1]>pt1[1]:

									    print "顺时针旋转"

									  else:

									    print "逆时针旋转"

									    angle=-angle

									  height = img.shape[0] # 原始图像高度

									  width = img.shape[1]  # 原始图像宽度

									  rotatemat = cv2.getrotationmatrix2d((width / 2, height / 2), angle, 1) # 按angle角度旋转图像

									  heightnew = int(width * fabs(sin(radians(angle))) + height * fabs(cos(radians(angle))))

									  widthnew = int(height * fabs(sin(radians(angle))) + width * fabs(cos(radians(angle))))

									  rotatemat[0, 2] += (widthnew - width) / 2

									  rotatemat[1, 2] += (heightnew - height) / 2

									  imgrotation = cv2.warpaffine(img, rotatemat, (widthnew, heightnew), bordervalue=(255, 255, 255))

									  cv2.imshow('rotateimg2', imgrotation)

									  cv2.waitkey(0)

									  # 旋转后图像的四点坐标

									  [[pt1[0]], [pt1[1]]] = np.dot(rotatemat, np.array([[pt1[0]], [pt1[1]], [1]]))

									  [[pt3[0]], [pt3[1]]] = np.dot(rotatemat, np.array([[pt3[0]], [pt3[1]], [1]]))

									  [[pt2[0]], [pt2[1]]] = np.dot(rotatemat, np.array([[pt2[0]], [pt2[1]], [1]]))

									  [[pt4[0]], [pt4[1]]] = np.dot(rotatemat, np.array([[pt4[0]], [pt4[1]], [1]]))

									  # 处理反转的情况

									  if pt2[1]>pt4[1]:

									    pt2[1],pt4[1]=pt4[1],pt2[1]

									  if pt1[0]>pt3[0]:

									    pt1[0],pt3[0]=pt3[0],pt1[0]

									  imgout = imgrotation[int(pt2[1]):int(pt4[1]), int(pt1[0]):int(pt3[0])]

									  cv2.imshow("imgout", imgout) # 裁减得到的旋转矩形框

									  cv2.waitkey(0)

									  return imgrotation # rotated image

									＃　根据四点画原矩形

									def drawrect(img,pt1,pt2,pt3,pt4,color,linewidth):

									  cv2.line(img, pt1, pt2, color, linewidth)

									  cv2.line(img, pt2, pt3, color, linewidth)

									  cv2.line(img, pt3, pt4, color, linewidth)

									  cv2.line(img, pt1, pt4, color, linewidth)

									#　读出文件中的坐标值

									def readtxt(directory,imagename,last):

									  filetxt=directory+"//rawlabel//"+imagename[:7]+last # txt文件名

									  gettxt=open(filetxt, 'r') # 打开txt文件

									  lines = gettxt.readlines()

									  length=len(lines)

									  for i in range(0,length,4):

									    pt2=list(map(float,lines[i].split(' ')[:2]))

									    pt1=list(map(float,lines[i+1].split(' ')[:2]))

									    pt4=list(map(float,lines[i+2].split(' ')[:2]))

									    pt3=list(map(float,re.split('\n| ',lines[i+3])[:2]))

									    # float转int

									    pt2=list(map(int,pt2))

									    pt1=list(map(int,pt1))

									    pt4=list(map(int,pt4))

									    pt3=list(map(int,pt3))

									    imgsrc = cv2.imread(imagename)

									    drawrect(imgsrc, tuple(pt1),tuple(pt2),tuple(pt3),tuple(pt4), (0, 0, 255), 2)

									    cv2.imshow("img", imgsrc)

									    cv2.waitkey(0)

									    rotate(imgsrc,pt1,pt2,pt3,pt4)

									if __name__=="__main__":

									  directory = "g://grasp//grapcode//trainimage//jpg//4"

									  last = 'cneg.txt'

									  imagename="pcd0247r.png"

									  readtxt(directory,imagename,last)