如何使用Python和OpenCV裁剪图像中的多个ROI

问题描述

我有一张从PDF转换为PNG的图像。转换后的图像包含我想使用OCR Tesseract提取的几个关键字。

现在，我需要手动确定ROI以裁剪选定的ROI。既然我要应用5个以上的ROI，那么应用ROI而不是通过反复尝试来找到确切位置的方法，最有效的方法是什么？

下面是代码：

    def cropped(self,event):

        #1st ROI
        y = 20
        x = 405
        h = 230
        w = 425

        #2nd ROI
        y1 = 30
        x1 = 305
        h1 = 330
        w1 = 525

        #open the converted image
        image = cv2.imread("Output.png")

        #perform image cropping
        crop_image = image[x:w,y:h]
        crop_image1 = image[x1:w1,y1:h1]
        
        #save the cropped image
        cv2.imwrite("Cropped.png",crop_image)
        cv2.imwrite("Cropped1.png",crop_image1)
        
        #open the cropped image and pass to the OCR engine
        im = cv2.imread("Cropped.png")
        im1 = cv2.imread("Cropped1.png")

        ## Do the text extraction here

解决方法

您可以使用鼠标事件根据位置选择多个ROI和作物

#!/usr/bin/env python3
import argparse
import cv2
import numpy as np
from PIL import Image
import os


drawing = False # true if mouse is pressed
ix,iy = -1,-1
refPt = []
img = ""
clone = ""
ROIRegion = []

# mouse callback function
def draw_rectangle(event,x,y,flags,param):
    global ix,iy,drawing,img,clone,refPt,ROIRegion
    if event == cv2.EVENT_LBUTTONDOWN:
        drawing = True
        ix,iy = x,y
        refPt = [(x,y)]
        ROIRegion.append(refPt)
        #clone = img.copy()

    elif event == cv2.EVENT_MOUSEMOVE:
        if drawing == True:
            img = clone.copy()
            cv2.rectangle(img,(ix,iy),(x,y),(0,255,0),3)
            a=x
            b=y
            if a != x | b != y:
                cv2.rectangle(img,-1)

    elif event == cv2.EVENT_LBUTTONUP:
        drawing = False
        refPt.append((x,y))
        img = clone.copy()
        cv2.rectangle(img,2)


ap = argparse.ArgumentParser()
ap.add_argument("-i","--image",required=True,help="Path to the image")
args = vars(ap.parse_args())
# load the image,clone it,and setup the mouse callback function
img = cv2.imread(args["image"])
img = np.array(img)
clone = img.copy()

cv2.namedWindow('image')
cv2.setMouseCallback('image',draw_rectangle)
while(1):
    cv2.imshow('image',img)

    k = cv2.waitKey(1) & 0xFF
    if k == ord("r"):
        del ROIRegion[-1]
        del refPt[-1]
        img = clone.copy()

    elif k == 27:
        break

#Do your cropping here
for region in range(len(ROIRegion)):
    cv2.rectangle(img,ROIRegion[region][0],ROIRegion[region][1],2)
    roi = clone[ROIRegion[region][0][1]:ROIRegion[region][1][1],ROIRegion[region][0][0]:ROIRegion[region][1][0]]
    roi = cv2.cvtColor(roi,cv2.COLOR_BGR2RGB)

这是Python / OpenCV中的一种方法。

阅读输入内容
框轮廓颜色的阈值
应用形态以确保封闭
获取外部轮廓
环绕每个轮廓，获取其边界框，在输入中裁剪区域并写入输出

输入：

import cv2
import numpy as np

# read image
img = cv2.imread('text_boxes.jpg')

# threshold on box outline color
lowerBound = (80,120,100)
upperBound = (160,200,180)
thresh = cv2.inRange(img,lowerBound,upperBound)

# apply morphology to ensure regions are filled and remove extraneous noise
kernel = np.ones((3,3),np.uint8)
thresh = cv2.morphologyEx(thresh,cv2.MORPH_CLOSE,kernel)

# get contours
contours = cv2.findContours(thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]

# get bounding boxes
i = 1
for cntr in contours:
    # get bounding boxes
    x,w,h = cv2.boundingRect(cntr)
    crop = img[y:y+h,x:x+w]
    cv2.imwrite("text_boxes_crop_{0}.png".format(i),crop)
    i = i + 1

# save threshold
cv2.imwrite("text_boxes_thresh.png",thresh)

# show thresh and result    
cv2.imshow("thresh",thresh)
cv2.waitKey(0)
cv2.destroyAllWindows()

阈值图像：

裁剪的图像：

opencv opencv python roi