OpenCV SelectiveSearch Segmentation

edit

whoa, 5000x4000 is really large, and it's taking a few minutes here on VGA , already

it's a bit unclear what "ROI proposals" (for what ?) means, can you explain ?

can you get away with upscaling ROIs taken from a resized (smaller) image ?

there's also the hfs module in contrib and maybe you can find a pretrained ENet (cnn segmentation) model for medical stuff..

Try this:

import cv2
import random

image = cv2.imread("deer.jpg")
print("[INFO]: Calculating candidate region of interest using Selective Search ...")  
ss = cv2.ximgproc.segmentation.createSelectiveSearchSegmentation()
ss.setBaseImage(image)
ss.switchToSelectiveSearchQuality()
rects = ss.process()

print("[INFO]: Found {} candidate region of interests".format(len(rects)))
for i in range(0, len(rects)):
    output = image.copy()
    for (x, y, w, h) in rects[i:i]:
        color = [random.randint(0, 255) for j in range(0, 3)]
        cv2.rectangle(output, (x, y), (x + w, y + h), color, 2)

    cv2.imshow("Deer Image", output)
    key = cv2.waitKey(0)  

    if key == ord("q"):
        break

U will have to downsized as @berak stating. I do not have 5kx4k. @berak, the link isn't working.

@supra56 - link updated, thanks for notice

Can u post image 5kx4k?