Detecting if an object from one image is in another image with OpenCV

Question

I have a sample image which contains an object, such as the earrings in the following image:

http://imgur.com/luj2Z

I then have a large candidate set of imag

Answer 1

In case someone comes along in the future, here's a small sample doing this with openCV. It's based on the opencv sample, but (in my opinion), this is a bit clearer, so I'm including it as well.

Tested with openCV 2.4.4

#!/usr/bin/env python

'''
Uses SURF to match two images.
  Finds common features between two images and draws them

Based on the sample code from opencv:
  samples/python2/find_obj.py

USAGE
  find_obj.py  
'''

import sys

import numpy
import cv2


###############################################################################
# Image Matching
###############################################################################

def match_images(img1, img2, img1_features=None, img2_features=None):
    """Given two images, returns the matches"""
    detector = cv2.SURF(3200)
    matcher = cv2.BFMatcher(cv2.NORM_L2)

    if img1_features is None:
        kp1, desc1 = detector.detectAndCompute(img1, None)
    else:
        kp1, desc1 = img1_features

    if img2_features is None:
        kp2, desc2 = detector.detectAndCompute(img2, None)
    else:
        kp2, desc2 = img2_features

    #print 'img1 - %d features, img2 - %d features' % (len(kp1), len(kp2))

    raw_matches = matcher.knnMatch(desc1, trainDescriptors=desc2, k=2)
    kp_pairs = filter_matches(kp1, kp2, raw_matches)
    return kp_pairs


def filter_matches(kp1, kp2, matches, ratio=0.75):
    """Filters features that are common to both images"""
    mkp1, mkp2 = [], []
    for m in matches:
        if len(m) == 2 and m[0].distance < m[1].distance * ratio:
            m = m[0]
            mkp1.append(kp1[m.queryIdx])
            mkp2.append(kp2[m.trainIdx])
    kp_pairs = zip(mkp1, mkp2)
    return kp_pairs


###############################################################################
# Match Diplaying
###############################################################################

def draw_matches(window_name, kp_pairs, img1, img2):
    """Draws the matches"""
    mkp1, mkp2 = zip(*kp_pairs)

    H = None
    status = None

    if len(kp_pairs) >= 4:
        p1 = numpy.float32([kp.pt for kp in mkp1])
        p2 = numpy.float32([kp.pt for kp in mkp2])
        H, status = cv2.findHomography(p1, p2, cv2.RANSAC, 5.0)

    if len(kp_pairs):
        explore_match(window_name, img1, img2, kp_pairs, status, H)


def explore_match(win, img1, img2, kp_pairs, status=None, H=None):
    """Draws lines between the matched features"""
    h1, w1 = img1.shape[:2]
    h2, w2 = img2.shape[:2]
    vis = numpy.zeros((max(h1, h2), w1 + w2), numpy.uint8)
    vis[:h1, :w1] = img1
    vis[:h2, w1:w1 + w2] = img2
    vis = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR)

    if H is not None:
        corners = numpy.float32([[0, 0], [w1, 0], [w1, h1], [0, h1]])
        reshaped = cv2.perspectiveTransform(corners.reshape(1, -1, 2), H)
        reshaped = reshaped.reshape(-1, 2)
        corners = numpy.int32(reshaped + (w1, 0))
        cv2.polylines(vis, [corners], True, (255, 255, 255))

    if status is None:
        status = numpy.ones(len(kp_pairs), numpy.bool_)
    p1 = numpy.int32([kpp[0].pt for kpp in kp_pairs])
    p2 = numpy.int32([kpp[1].pt for kpp in kp_pairs]) + (w1, 0)

    green = (0, 255, 0)
    red = (0, 0, 255)
    for (x1, y1), (x2, y2), inlier in zip(p1, p2, status):
        if inlier:
            col = green
            cv2.circle(vis, (x1, y1), 2, col, -1)
            cv2.circle(vis, (x2, y2), 2, col, -1)
        else:
            col = red
            r = 2
            thickness = 3
            cv2.line(vis, (x1 - r, y1 - r), (x1 + r, y1 + r), col, thickness)
            cv2.line(vis, (x1 - r, y1 + r), (x1 + r, y1 - r), col, thickness)
            cv2.line(vis, (x2 - r, y2 - r), (x2 + r, y2 + r), col, thickness)
            cv2.line(vis, (x2 - r, y2 + r), (x2 + r, y2 - r), col, thickness)
    vis0 = vis.copy()
    for (x1, y1), (x2, y2), inlier in zip(p1, p2, status):
        if inlier:
            cv2.line(vis, (x1, y1), (x2, y2), green)

    cv2.imshow(win, vis)

###############################################################################
# Test Main
###############################################################################

if __name__ == '__main__':
    if len(sys.argv) < 3:
        print "No filenames specified"
        print "USAGE: find_obj.py  "
        sys.exit(1)

    fn1 = sys.argv[1]
    fn2 = sys.argv[2]

    img1 = cv2.imread(fn1, 0)
    img2 = cv2.imread(fn2, 0)

    if img1 is None:
        print 'Failed to load fn1:', fn1
        sys.exit(1)

    if img2 is None:
        print 'Failed to load fn2:', fn2
        sys.exit(1)

    kp_pairs = match_images(img1, img2)

    if kp_pairs:
        draw_matches('find_obj', kp_pairs, img1, img2)
    else:
        print "No matches found"

    cv2.waitKey()
    cv2.destroyAllWindows()