How to detect free space between two detected windows - python-3.x

Question

I used YOLOv3 to detect windows on the building. Each window shows with a bounding box around, also I extracted coordinates of each window [top_left, bottom_left, top_right, bottom_right]. now I want to find free space[wall] between all the windows. I put the coordinates of each window in a Dict.
when I set the values manually it works for each window for instance:
p1 = points_list[0][2] # top_left window1
p2 = points_list[1][1] # bottom_left window2
cv2.rectangle(img, p1, p2, (255, 0, 255), -1)
, but how can I make it automatically to find walls.
Here is my first output image, the detected wall shows by pink color.
here also I have added a sample of my code.
def bb_to_rect(x, y, w, h):
top_left = (x, y)
top_right = (x + w, y)
bottom_left = (x, y + h)
bottom_right = (x + w, y + h)
return top_left, bottom_left, top_right, bottom_right
def draw_bounding_box(img, font, boxes, confidences, colors):
indices = cv2.dnn.NMSBoxes(boxes, confidences, CONF_THRESHOLD, NMS_THRESHOLD)
points_list={}
count = 0
for i in range(len(boxes)):
if i in indices:
(x, y, w, h) = boxes[i]
label = "{}:{:.2f}%".format(classes[class_ids[i]], confidences[i] * 100)
color = colors[class_ids[i]]
cv2.rectangle(img, (x, y), (x + w, y + h), color, 2)
cv2.putText(img, str(i), (x, y), cv2.FONT_HERSHEY_TRIPLEX,
.5, (255, 255, 0), 1, cv2.LINE_AA)
top_left, bottom_left, top_right, bottom_right = bb_to_rect(x, y, w, h)
points_list[count] = [top_left, bottom_left, top_right, bottom_right]
count += 1
cv2.circle(img, (x + w, y), 3, (50, 100, 0), -1) # top Right
cv2.circle(img, (x + w, y + h), 3, (0, 0, 255), -1) # bottom Right
cv2.circle(img, (x, y), 3, (0, 255, 100), -1) # top left
cv2.circle(img, (x, y + h), 3, (255, 0, 255), -1) # bottom left
return img, points_list
if __name__ == "__main__":
net, output_layers, colors, classes = load_yolo_model()
img, height, width = load_img(IMAGES_PATH)
outs = create_blob(img, net, output_layers)
boxes, class_ids, confidences, centroids = detect_obj(outs, height, width, img)
img, points_list = draw_bounding_box(img, FONT, boxes, confidences, colors)
p1 = points_list[0][2] # window0 to window1
p2 = points_list[1][1]
p2_1 = points_list[1][2] # window1 to window2
p2_2 = points_list[2][1]
p3_1 = points_list[3][2] # window3 to window5
p5_2 = points_list[5][1]
cv2.rectangle(img, p1, p2, (255, 0, 255), -1)
cv2.rectangle(img, p2_1, p2_2, (255, 0, 255), -1)
cv2.rectangle(img, p3_1, p5_2, (255, 0, 255), -1)
cv2.imshow('out', img)
cv2.waitKey(0)
Also if you see the photo you will see the windows detected randomly and the Id number for each window does not order. How can I solve this problem? thanks in advance for helping:)

Answer 1

Have you tried Image Segmentation to find the objects on wall? then with a simple trick like finding the countors you can measure the distance between the objects like windows as you said.
2nd trick:
I've got another easy way which may help you:
first of all, find the edges using canny edg detection, the with dilate function fill the middle space of vertical edges between windows then by Hough Line Detection you can find the vertical lines of windows, and get the distance between the y axis of vertical lines of the wall.