int main(int argc, char **argv)
{
if (argc < 4 || argc > 8) {
printf("Usage: %s <list.in> <tree.in> <tree.out> [use_tfidf:1] "
"[normalize:1] [start_id:0] [distance_type:1]\n",
argv[0]);
return 1;
}
double min_feature_scale = 1.4;
bool use_tfidf = true;
bool normalize = true;
char *list_in = argv[1];
char *tree_in = argv[2];
char *tree_out = argv[3];
DistanceType distance_type = DistanceMin;
int start_id = 0;
if (argc >= 5)
use_tfidf = atoi(argv[4]);
if (argc >= 6)
normalize = atoi(argv[5]);
if (argc >= 7)
start_id = atoi(argv[6]);
if (argc >= 8)
distance_type = (DistanceType) atoi(argv[7]);
switch (distance_type) {
case DistanceDot:
printf("[VocabMatch] Using distance Dot\n");
break;
case DistanceMin:
printf("[VocabMatch] Using distance Min\n");
break;
default:
printf("[VocabMatch] Using no known distance!\n");
break;
}
FILE *f = fopen(list_in, "r");
if (f == NULL) {
printf("Error opening file %s for reading\n", list_in);
return 1;
}
std::vector<std::string> key_files;
char buf[256];
while (fgets(buf, 256, f)) {
/* Remove trailing newline */
if (buf[strlen(buf) - 1] == '\n')
buf[strlen(buf) - 1] = 0;
key_files.push_back(std::string(buf));
}
printf("[VocabBuildDB] Reading tree %s...\n", tree_in);
fflush(stdout);
VocabTree tree;
tree.Read(tree_in);
#if 1
tree.Flatten();
#endif
tree.m_distance_type = distance_type;
tree.SetInteriorNodeWeight(0.0);
/* Initialize leaf weights to 1.0 */
tree.SetConstantLeafWeights();
const int dim = 128;
int num_db_images = (int) key_files.size();
unsigned long count = 0;
tree.ClearDatabase();
for (int i = 0; i < num_db_images; i++) {
int num_keys = 0;
unsigned char *keys = ReadAndFilterKeys(key_files[i].c_str(),
dim, min_feature_scale,
0, num_keys);
printf("[VocabBuildDB] Adding vector %d (%d keys)\n",
start_id + i, num_keys);
tree.AddImageToDatabase(start_id + i, num_keys, keys);
if (num_keys > 0)
delete [] keys;
}
printf("[VocabBuildDB] Pushed %lu features\n", count);
fflush(stdout);
if (use_tfidf)
tree.ComputeTFIDFWeights(num_db_images);
if (normalize)
tree.NormalizeDatabase(start_id, num_db_images);
printf("[VocabBuildDB] Writing tree...\n");
tree.Write(tree_out);
// char filename[256];
// sprintf(filename, "vectors_%03d.txt", start_id);
// tree.WriteDatabaseVectors(filename, start_id, num_db_images);
return 0;
}
// compare images feature using db
int VocabCompare(int argc, char **argv)
{
if (argc != 5 && argc != 6)
{
printf("Usage: %s <tree.in> <image1.key> <image2.key> <matches.out> [distance_type]\n", argv[0]);
return 1;
}
char *tree_in = argv[1];
char *image1_in = argv[2];
char *image2_in = argv[3];
char *matches_out = argv[4];
DistanceType distance_type = DistanceMin;
if (argc >= 6)
distance_type = (DistanceType)atoi(argv[5]);
switch (distance_type) {
case DistanceDot:
printf("[VocabMatch] Using distance Dot\n");
break;
case DistanceMin:
printf("[VocabMatch] Using distance Min\n");
break;
default:
printf("[VocabMatch] Using no known distance!\n");
break;
}
printf("[VocabBuildDB] Reading tree %s...\n", tree_in); fflush(stdout);
VocabTree tree;
tree.Read(tree_in);
printf("[VocabCompare] Flattening tree...\n");
tree.Flatten();
tree.m_distance_type = distance_type;
tree.SetInteriorNodeWeight(0.0);
/* Initialize leaf weights to 1.0 */
tree.SetConstantLeafWeights();
const int dim = 128;
tree.ClearDatabase();
int num_keys_1 = 0, num_keys_2 = 0;
unsigned char *keys1 = ReadKeys(image1_in, dim, num_keys_1);
unsigned char *keys2 = ReadKeys(image2_in, dim, num_keys_2);
unsigned long *ids1 = new unsigned long[num_keys_1];
unsigned long *ids2 = new unsigned long[num_keys_2];
printf("[VocabCompare] Adding image 0 (%d keys)\n", num_keys_1);
tree.AddImageToDatabase(0, num_keys_1, keys1, ids1);
if (num_keys_1 > 0)
delete[] keys1;
printf("[VocabCompare] Adding image 1 (%d keys)\n", num_keys_2);
tree.AddImageToDatabase(1, num_keys_2, keys2, ids2);
if (num_keys_2 > 0)
delete[] keys2;
// tree.ComputeTFIDFWeights();
tree.NormalizeDatabase(0, 2);
//Find collisions among visual word IDs
std::multimap<unsigned long, unsigned int> word_map;
for (unsigned int i = 0; i < (unsigned int)num_keys_1; i++)
{
printf("0 %d -> %lu\n", i, ids1[i]);
std::pair<unsigned long, unsigned int> elem(ids1[i], i);
word_map.insert(elem);
}
//Count number of matches
int num_matches = 0;
for (unsigned int i = 0; i < (unsigned int)num_keys_2; i++)
{
unsigned long id = ids2[i];
printf("1 %d -> %lu\n", i, ids2[i]);
std::pair<std::multimap<unsigned long, unsigned int>::iterator, std::multimap<unsigned long, unsigned int>::iterator> ret;
ret = word_map.equal_range(id);
unsigned int size = 0;
std::multimap<unsigned long, unsigned int>::iterator iter;
for (iter = ret.first; iter != ret.second; iter++)
size++, num_matches++;
if (size > 0)
printf("size[%lu] = %d\n", id, size);
}
printf("number of matches: %d\n", num_matches); fflush(stdout);
FILE *f = fopen(matches_out, "w");
if (f == NULL)
{
printf("Error opening file %s for writing\n", matches_out);
return 1;
}
fprintf(f, "%d\n", num_matches);
/* Write matches */
for (unsigned int i = 0; i < (unsigned int)num_keys_2; i++)
{
unsigned long id = ids2[i];
std::pair<std::multimap<unsigned long, unsigned int>::iterator, std::multimap<unsigned long, unsigned int>::iterator> ret;
ret = word_map.equal_range(id);
std::multimap<unsigned long, unsigned int>::iterator iter;
for (iter = ret.first; iter != ret.second; iter++)
fprintf(f, "%d %d\n", iter->second, i);
}
fclose(f);
// printf("[VocabBuildDB] Writing tree...\n");
// tree.Write(tree_out);
return 0;
}
int main(int argc, char **argv)
{
const int dim = 128;
if (argc != 6 && argc != 7 && argc != 8 && argc != 9 && argc != 10 &&
argc != 11) {
printf("Usage: %s <tree.in> <db.in> <query.in> <num_nbrs> "
"<match-script.out> [leaves_only] [distance_type] [normalize] "
"[min_feature_scale] [max_keys]\n",
argv[0]);
return 1;
}
char *tree_in = argv[1];
char *db_in = argv[2];
char *query_in = argv[3];
int num_nbrs = atoi(argv[4]);
char *matches_out = argv[5];
bool leaves_only = false;
bool normalize = true;
double min_feature_scale = 0.0;
DistanceType distance_type = DistanceMin;
int max_keys = 0;
if (argc >= 7) {
if (atoi(argv[6]) != 0)
leaves_only = true;
}
if (argc >= 8)
distance_type = (DistanceType) atoi(argv[7]);
if (argc >= 9)
if (atoi(argv[8]) == 0)
normalize = false;
if (argc >= 10) {
min_feature_scale = atof(argv[9]);
}
if (argc >= 11) {
max_keys = atoi(argv[10]);
}
if (leaves_only) {
printf("[VocabMatch] Scoring with leaves only\n");
} else {
printf("[VocabMatch] Scoring with all nodes\n");
}
printf("[VocabMatch] Using tree %s\n", tree_in);
printf("[VocabMatch] min_feature_scale = %0.3f\n", min_feature_scale);
printf("[VocabMatch] max_keys = %d\n", max_keys);
switch (distance_type) {
case DistanceDot:
printf("[VocabMatch] Using distance Dot\n");
break;
case DistanceMin:
printf("[VocabMatch] Using distance Min\n");
break;
default:
printf("[VocabMatch] Using no known distance!\n");
break;
}
/* Read the tree */
printf("[VocabMatch] Reading tree...\n");
fflush(stdout);
clock_t start = clock();
VocabTree tree;
tree.Read(tree_in);
clock_t end = clock();
printf("[VocabMatch] Read tree in %0.3fs\n",
(double) (end - start) / CLOCKS_PER_SEC);
#if 1
tree.Flatten();
#endif
tree.SetDistanceType(distance_type);
if (leaves_only) {
tree.SetInteriorNodeWeight(atoi(argv[6]) - 1, 0.0);
// #define CONSTANT_WEIGHTS
#ifdef CONSTANT_WEIGHTS
tree.SetConstantLeafWeights();
#endif
}
/* Read the database keyfiles */
FILE *f = fopen(db_in, "r");
std::vector<std::string> db_files;
char buf[256];
while (fgets(buf, 256, f)) {
/* Remove trailing newline */
if (buf[strlen(buf) - 1] == '\n')
buf[strlen(buf) - 1] = 0;
db_files.push_back(std::string(buf));
}
fclose(f);
/* Read the query keyfiles */
f = fopen(query_in, "r");
std::vector<std::string> query_files;
std::vector<int> query_indices;
while (fgets(buf, 256, f)) {
/* Remove trailing newline */
if (buf[strlen(buf) - 1] == '\n')
buf[strlen(buf) - 1] = 0;
char keyfile[256];
int index;
sscanf(buf, "%d %s", &index, keyfile);
query_files.push_back(std::string(keyfile));
query_indices.push_back(index);
}
fclose(f);
/* Populate the database */
printf("[VocabMatch] Populating database...\n");
fflush(stdout);
int num_db_images = db_files.size();
int num_query_images = query_files.size();
/* Now score each query keyfile */
printf("[VocabMatch] Scoring query images...\n");
fflush(stdout);
float *scores = new float[num_db_images];
double *scores_d = new double[num_db_images];
int *perm = new int[num_db_images];
FILE *f_match = fopen(matches_out, "w");
if (f_match == NULL) {
printf("[VocabMatch] Error opening file %s for writing\n",
matches_out);
return 1;
}
for (int i = 0; i < num_query_images; i++) {
int index_i = query_indices[i];
start = clock();
/* Clear scores */
for (int j = 0; j < num_db_images; j++)
scores[j] = 0.0;
unsigned char *keys;
int num_keys;
keys = ReadAndFilterKeys(query_files[i].c_str(), dim,
min_feature_scale, max_keys, num_keys);
tree.ScoreQueryKeys(num_keys, /*i,*/ true, keys, scores);
end = clock();
printf("[VocabMatch] Scored image %s (%d keys) in %0.3fs\n",
query_files[i].c_str(), num_keys,
(double) (end - start) / CLOCKS_PER_SEC);
#if 0
for (int j = 0; j < num_db_images; j++) {
/* Normalize scores */
if (magnitudes[j] > 0.0)
scores[j] /= magnitudes[j];
else
scores[j] = 0.0;
}
#endif
/* Find the top scores */
for (int j = 0; j < num_db_images; j++) {
scores_d[j] = (double) scores[j];
}
qsort_descending();
qsort_perm(num_db_images, scores_d, perm);
// assert(is_sorted(num_db_images, scores_d));
int top = MIN(num_nbrs+1, num_db_images);
for (int j = 0; j < top; j++) {
if (perm[j] == index_i)
continue;
fprintf(f_match, "%d %d %0.5e\n", index_i, perm[j], scores_d[j]);
fflush(f_match);
}
fflush(stdout);
delete [] keys;
}
fclose(f_match);
delete [] scores;
delete [] scores_d;
delete [] perm;
return 0;
}
// Building a database with a vocabulary tree
int VocabDB(char *list_in, char *tree_in, char *db_out, int use_tfidf = 1, int normalize = 1, int start_id = 0, DistanceType distance_type = DistanceMin)
{
double min_feature_scale = 1.4;
switch (distance_type) {
case DistanceDot:
printf("[VocabMatch] Using distance Dot\n");
break;
case DistanceMin:
printf("[VocabMatch] Using distance Min\n");
break;
default:
printf("[VocabMatch] Using no known distance!\n");
break;
}
FILE *f = fopen(list_in, "r");
if (f == NULL) {
printf("Error opening file %s for reading\n", list_in);
return 1;
}
std::vector<std::string> key_files;
char buf[256];
while (fgets(buf, 256, f))
{
/* Remove trailing newline */
if (buf[strlen(buf) - 1] == '\n')
buf[strlen(buf) - 1] = 0;
key_files.push_back(std::string(buf));
}
printf("[VocabBuildDB] Reading tree %s...\n", tree_in);
fflush(stdout);
VocabTree tree;
tree.Read(tree_in);
tree.Flatten();
tree.m_distance_type = distance_type;
tree.SetInteriorNodeWeight(0.0);
//Initialize leaf weights to 1.0
tree.SetConstantLeafWeights();
const int dim = 128;
int num_db_images = (int)key_files.size();
unsigned long count = 0;
tree.ClearDatabase();
for (int i = 0; i < num_db_images; i++)
{
int num_keys = 0;
unsigned char *keys = ReadAndFilterKeys(key_files[i].c_str(), dim, min_feature_scale, 0, num_keys);
printf("[VocabBuildDB] Adding vector %d (%d keys)\n", start_id + i, num_keys);
tree.AddImageToDatabase(start_id + i, num_keys, keys);
if (num_keys > 0)
delete[] keys;
}
printf("[VocabBuildDB] Pushed %lu features\n", count);
fflush(stdout);
if (use_tfidf == 1)
tree.ComputeTFIDFWeights(num_db_images);
if (normalize == 1)
tree.NormalizeDatabase(start_id, num_db_images);
printf("[VocabBuildDB] Writing database ...\n");
tree.Write(db_out);
// char filename[256];
// sprintf(filename, "vectors_%03d.txt", start_id);
// tree.WriteDatabaseVectors(filename, start_id, num_db_images);
return 0;
}