Constract bounding boxes from encoded pixels in python

Question

What is the efficient way to constract bounding boxes for an objeject given the encoded pixel of that object. I am trying to convert a task from segmentation to object detection in yolo. Any suggestions are welcomed.

question from:https://stackoverflow.com/questions/66055809/constract-bounding-boxes-from-encoded-pixels-in-python

Answer 1

If you have the points of the segmentation then you can find the extents of the points by iterating through and recording the lowest and highest values of [x,y]. This will give you the the top left and bottom right corners.

If you're trying to work backwards from a colored, segmented image then you can use opencv to threshold the colors and get boxes from the blobs like this:

import cv2
import numpy as np

# load image
img = cv2.imread("mask.png");
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY);

# threshold
thresh = cv2.inRange(gray, 100, 255);

# contour
_, contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE);

# draw rectangle
x,y,w,h = cv2.boundingRect(contours[0]);
cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2);

# show
cv2.imshow("box", img);
cv2.imshow("Thresh", thresh);
cv2.waitKey(0);

# save
cv2.imwrite("boxed.png", img);