How to scan room contour data from a floor plan using OpenCV or deep learning?

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I want to find every room's accurate contour data such as bedrooms and living rooms, using OpenCV and Python, but can't do it well.maybe use CNN?

I tried to use cv2.erode, cv2.dilate, and cv2.findContours.

Here is an example of a floor plan to scan: enter image description here I really expect result contains all the space of the special room, including furniture, but can not contain space in other rooms, such as the bedroom can not contain the space of the living room, and the outline can not contain curves. I except just like this: enter image description here

Here is my python code:

import cv2
import random
img = cv2.imread('./lj_hx/zz.jpg')

gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

_, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)

cv2.imshow("thresh", thresh)

mor_img = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, (5, 5), iterations=3)

_, contours, _ = cv2.findContours(mor_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

sorted_contours = sorted(contours, key=cv2.contourArea, reverse=True)

for c in sorted_contours[1:]:
    area = cv2.contourArea(c)
    if area > 6000:
        cv2.drawContours(img, [c], -1, (random.randrange(0, 255), random.randrange(0, 256), random.randrange(0, 255)), 3)

cv2.imshow("mor_img", mor_img)
cv2.imshow("img", img)

cv2.waitKey(0)
contour computer-vision opencv image-processing python
1 Answers

What exactly is the part that you "can't do [...] well"? I tried your code, plotted the areas in the center of the rooms and it looks pretty well (except for 1 bedroom, where the bed is not included). Is that what you meant, or didn't you get this far?

import cv2
import random
img = cv2.imread('./lj_hx/zz.jpg')

gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)

_, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)

cv2.imshow("thresh", thresh)

mor_img = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, (3, 3), iterations=3)

contours, hierarchy = cv2.findContours(mor_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) # I addapted this part of the code. This is how my version works (2.4.16), but it could be different for OpenCV 3 

sorted_contours = sorted(contours, key=cv2.contourArea, reverse=True)

for c in sorted_contours[1:]:
    area = cv2.contourArea(c)
    if area > 6000:
        print area
        cv2.drawContours(img, [c], -1, (random.randrange(0, 255), random.randrange(0, 255), random.randrange(0, 255)), 3)
        x, y, w, h = cv2.boundingRect(c) # the lines below are for getting the approximate center of the rooms
        cx = x + w / 2
        cy = y + h / 2
        cv2.putText(img,str(area),(cx,cy), cv2.FONT_HERSHEY_SIMPLEX, .5,(255,0,0),1,cv2.CV_AA)

cv2.imshow("mor_img", mor_img)
cv2.imshow("img", img)
cv2.waitKey(0)
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