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How to use bag of words to predict an image?


Can anyone please tell me how to use the bag of words function in opencv? I want to use it on a folder of images; to train it such that if I use a sample image from that folder it should be able to recognize it.

While reading the only example online of this I was able to make a library / vocabulary. The code I used for that is below:

Ptr<FeatureDetector> features = FeatureDetector::create("SIFT");
Ptr<DescriptorExtractor> descriptors = DescriptorExtractor::create("SIFT");
Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("FlannBased");

//defining terms for bowkmeans trainer
TermCriteria tc(MAX_ITER + EPS, 10, 0.001);
int dictionarySize = 1000;
int retries = 1;
int flags = KMEANS_PP_CENTERS;
BOWKMeansTrainer bowTrainer(dictionarySize, tc, retries, flags);

BOWImgDescriptorExtractor bowDE(descriptors, matcher);

//training data now
Mat features;
Mat img = imread("c:\\1.jpg", 0);
Mat img2 = imread("c:\\2.jpg", 0);
vector<KeyPoint> keypoints, keypoints2;
features->detect(img, keypoints);
descriptor->compute(img, keypoints, features);
Mat features2;
descripto->compute(img2, keypoints2, features2);

Mat dictionary = bowTrainer.cluster();

Now I believe this would create the dictionary. So is the system now trained? or will I have to use one of the machine learning functions to train it? If so can some one please give me a brief example of it?

Thank you