コード例 #1
0
void glintFinder::smoothBlob(ofxCvBlob& blob, int smoothingSize, float smoothingAmount) {
    vector<ofPoint> ref = blob.pts;
    vector<ofPoint>& cur = blob.pts;
    int n = cur.size();
    for(int i = 0; i < n; i++) {
        cur[i].set(0, 0);
        float weightSum = 0;
        for(int j = 1; j <= smoothingSize; j++) {
            int leftPosition = (n + i - j) % n;
            int rightPosition = (i + j) % n;
            ofPoint& left = ref[leftPosition];
            ofPoint& right = ref[rightPosition];

            float weight = ofMap(j, 0, smoothingSize, 1, smoothingAmount);
            weightSum += weight;
            cur[i] += (left + right) * weight;
        }

        ofPoint& center = ref[i];
        cur[i] += center;
        cur[i] /= 1 + 2 * weightSum;
    }

    recomputeCentroid(blob);
}
コード例 #2
0
ファイル: kmeans.cpp プロジェクト: ivanzamanov/kmeans
void selectSeeds(cluster* clusters, entryList &l, int k) {
	int index = 0;
	for(int i=0; i<l.size(); i++) {
		index = i % k;
		cluster &cl = clusters[index];
		article_entry* e = l.get(i);
		cl.members.add(e);
	}
	printf("Computing centroids ");
	for(int i=0; i<k; i++) {
		printf("%d ", i);
		recomputeCentroid(clusters[i]);
	}
	printf("\n");
}
コード例 #3
0
ファイル: kmeans.cpp プロジェクト: ivanzamanov/kmeans
void clusterize(int k, entryList &l) {
	printf("Clusterizing in %d clusters\n", k);
	cluster *clusters = new cluster[k];
	selectSeeds(clusters, l, k);
	double RSS = printRSS(clusters, k);
	double prevRSS = 1e+20;

	int iterations = 0;
	while(iterations < MAX_ITERATIONS && (prevRSS - RSS) > THRESHOLD) {
		iterations++;
		printf("Iteration %d\n", iterations);
		// Clear cluster members.
		for(int i=0; i<k; i++)
			clusters[i].members.clear();

		// Find the best cluster for each entry
		// and add as a member
		for(int i=0; i<l.size(); i++) {
			article_entry* entry = l.get(i);
			cluster& cl = findBestCluster(clusters, k, entry->v);
			cl.members.add(entry);
		}

		// Recompute centroids
		printf("Computing centroids ");
		for(int i=0; i<k; i++) {
			printf("%d ", i);
			recomputeCentroid(clusters[i]);
		}
		printf("\n");

		prevRSS = RSS;
		RSS = printRSS(clusters, k);
	}

	delete[] clusters;
}