Is it possible to construct my own DMatch list in python?

I’ve done sift descriptor matching and RANSAC algorithm .
Now i got a list of coordinates.
I want to see if there’s a difference , cv.drawMatches() requires a list of DMatch data.
I’m not sure if This tutorial did the same thing.

if len(good)>MIN_MATCH_COUNT:
    src_pts = np.float32([ kp1[m.queryIdx].pt for m in good ]).reshape(-1,1,2)
    dst_pts = np.float32([ kp2[m.trainIdx].pt for m in good ]).reshape(-1,1,2)
    M, mask = cv.findHomography(src_pts, dst_pts, cv.RANSAC,5.0)
    matchesMask = mask.ravel().tolist()
    h,w = img1.shape
    pts = np.float32([ [0,0],[0,h-1],[w-1,h-1],[w-1,0] ]).reshape(-1,1,2)
    dst = cv.perspectiveTransform(pts,M)
    # why draw this line?
    img2 = cv.polylines(img2,[np.int32(dst)],True,255,3, cv.LINE_AA)
    print( "Not enough matches are found - {}/{}".format(len(good), MIN_MATCH_COUNT) )
    matchesMask = None

draw_params = dict(matchColor = (0,255,0), # draw matches in green color
                   singlePointColor = None,
                   matchesMask = matchesMask, # draw only inliers
                   flags = 2)
img3 = cv.drawMatches(img1,kp1,img2,kp2,good,None,**draw_params)

sure you can do that !

that’s a bit useless here, you’ll need the indices into the original keypoint lists (from detect()) (m.queryIdx, m.trainIdx in the ex.), also the distance (from ransac ?). then its a simple:

dm = []
for whatever:
  dm.append(cv2.DMatch(idx1, idx2, distance))

you also need a list of bools (inlier or not), matchesMask in the tutorial.

it’s the white box around the target in the right image, hard to see :}

1 Like

Thanks again ! Exactly what i want !