Detect rectangles in OpenCV (4.2.0) using Python (3.7),

Question

I am working on a personal project where I detect rectangles (all the same dimensions) and then place those rectangles inside a list in the same order (top-bottom) and then process the information inside each rectangle using some function. Below is my test image.

I have managed to detect the rectangle of interest, however I keep getting other rectangles that I don't want. As you can see I only want the three rectangles with the information (6,9,3) into a list.

My code

import cv2

width=700
height=700
y1=0
y2=700
x1=500
x2=700
img=cv2.imread('test.jpg') #read image
img=cv2.resize(img,(width,height)) #resize image
roi = img[y1:y2, x1:x2] #region of interest i.e where the rectangles will be
gray = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY) #convert roi into gray
Blur=cv2.GaussianBlur(gray,(5,5),1) #apply blur to roi
Canny=cv2.Canny(Blur,10,50) #apply canny to roi

#Find my contours
contours =cv2.findContours(Canny,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)[0]

#Loop through my contours to find rectangles and put them in a list, so i can view them individually later.
cntrRect = []
for i in contours:
        epsilon = 0.05*cv2.arcLength(i,True)
        approx = cv2.approxPolyDP(i,epsilon,True)
        if len(approx) == 4:
            cv2.drawContours(roi,cntrRect,-1,(0,255,0),2)
            cv2.imshow('Roi Rect ONLY',roi)
            cntrRect.append(approx)



cv2.waitKey(0)
cv2.destroyAllWindows()

Solution

There is a feature in Contour called cv2.contourArea for which your contour dimensions are input like this cv2.contourArea(contours) . You can use the condition,

if cv2.contourArea(contours)>#Rectangle area

By using this your problem will be solved

Comments

[Alan Jones]

I have used that function, however I get 4 large rectangles instead of 3.

[Sreevathsabr]

@AlanJones what is the #Rectangle area you are providing? and are adding it in your if Statement with and keyword or any other way ?

[Alan Jones]

I am looping through all the areas to see what the area of each contour is. That is why I see 4 large areas instead of three (as expected).