Hi,
I am trying to use OpenCV (4.1.2) SelectiveSearch segmentation in order to generate ROI proposals for really large images (e.g. 5000x4000). Following code takes too much time to process one image:
print("[INFO]: Calculating candidate region of interest using Selective Search ...")
ss = cv2.ximgproc.segmentation.createSelectiveSearchSegmentation()
ss.setBaseImage(img_0)
ss.switchToSelectiveSearchFast()
rects = ss.process()
print("[INFO]: Found {} candidate region of interests".format(len(rects)))
proposed_rects =[]
for (x, y, w, h) in rects:
proposed_rects.append((x, y, x + w, y +h))
As you can assume, I am using Python. Any suggestions in which I could increase performance of my results?
I am using this for Medical Images, so if there is any suggestion what can I do to tweak perforamnce of generating better ROI proposals I would love to hear it. Doesnt have to be selective search.