def load_model():
ivf = InvertedFiles()
ivf_model = load_mat_with_cache(sett.cfg.COARSE_MODEL)["ivf"]
pq_model_mat = load_mat_with_cache(sett.cfg.PQ_MODEL)["pq"]
# ivf.quan = Quantizer.init_model_with_mat(pq_model_mat)
ivf.quan = PQ.init_model_with_mat(pq_model_mat)
ivf.codewords = ivf_model[0][0]["coa_centroids"]
ivf.n_words = ivf_model[0][0]["coarsek"][0][0]
return ivf
def search_exhasutive(imdb, keyword):
categories = keyword.split(" ")
cate_ids = []
for cate in categories:
try:
cate_id = PASCAL_CATEGORIES.index(cate)
cate_ids.append(cate_id)
except ValueError:
pass
if not cate_ids:
cate_ids = [1]
print (cate_ids)
start_at = time.time()
ivf = InvertedFiles.load_model()
ivf.load_data()
pq_model_mat = load_mat_with_cache(sett.cfg.PQ_MODEL)["pq"]
# q = Quantizer.init_model_with_mat(pq_model_mat)
q = PQ.init_model_with_mat(pq_model_mat)
weights = load_mat_with_cache(sett.cfg.TRAINED_SVM)["weight"]
ids = set()
db = load_featdb()
start_at = time.time()
for cate_id in cate_ids:
svm = weights[:, cate_id]
if USE_IVF:
idx = ivf.search_candidates(svm, 32)
else:
idx = pqsvm(svm, q, imdb)
id_tmp = db["ids"][idx]
if len(ids) == 0:
ids = set(id_tmp)
else:
ids = ids.intersection(id_tmp)
print ("IVF:{0}".format(time.time() - start_at)) + "[sec]"
# ids = db['ids'][list(ids)]
return list(ids)