def do_search(image_encoder, table_name, img_path, top_k):
try:
#print(top_k)
detector = Detector()
run(detector, img_path)
vect, obj_images = get_object_vector(image_encoder,
img_path + '/object')
#print("search...after detect:", len(vect), obj_images)
index_client = milvus_client()
#vect = normaliz_vec(vect)
status, results = search_vectors(index_client, table_name, vect, top_k)
# print(status, results)
vids = []
dis = []
for result in results:
for j in result:
vids.append(j.id)
dis.append(j.distance)
res_id = [x for x in query_name_from_ids(vids)]
#print("------------------res", vids, dis, res_id)
shutil.rmtree(img_path + '/object')
return res_id, dis
except Exception as e:
logging.error(e)
return "Fail with error {}".format(e)
def do_search_logo(image_encoder, index_client, conn, cursor, table_name, filename):
detector = Detector()
if not table_name:
table_name = LOGO_TABLE
prefix = filename.split("/")[2].split(".")[0] + "-" + uuid.uuid4().hex
images = extract_frame(filename, 1, prefix)
run(detector, DATA_PATH + '/' + prefix)
vectors, obj_images = get_object_vector(image_encoder, DATA_PATH + '/' + prefix + '/object')
results = search_vectors(index_client, table_name, vectors, "L2")
info, times = get_object_info(conn, cursor, table_name, results, obj_images)
return info, times
def do_search(table_name, img_path, model, milvus_client, mysql_cli):
try:
if not table_name:
table_name = DEFAULT_TABLE
detector = Detector()
run(detector, img_path)
vecs = get_object_vector(model, img_path + '/object')
# feat = model.resnet50_extract_feat(img_path)
results = milvus_client.search_vectors(table_name, vecs, TOP_K)
ids = []
distances = []
for result in results:
for j in result:
ids.append(j.id)
distances.append(j.distance)
# res_id = [x for x in query_name_from_ids(vids)]
# vids = [str(x.id) for x in vectors[0]]
paths = mysql_cli.search_by_milvus_ids(ids, table_name)
# distances = [x.distance for x in vectors[0]]
shutil.rmtree(img_path)
return paths, distances
except Exception as e:
LOGGER.error(" Error with search : {}".format(e))
sys.exit(1)
def do_load(table_name, database_path, model, mil_cli, mysql_cli):
detector = Detector()
if not table_name:
table_name = DEFAULT_TABLE
cache = Cache(CACHE_DIR)
result_images, object_num = run(detector, database_path)
vectors = get_object_vector(cache, model, database_path + "/object")
ids = mil_cli.insert(table_name, vectors)
mil_cli.create_index(table_name)
shutil.rmtree(database_path + "/object")
imgs = get_imgs_path(database_path)
imgs.sort()
matched_imgs = match_ids_and_imgs(imgs, object_num)
mysql_cli.create_mysql_table(table_name)
mysql_cli.load_data_to_mysql(table_name, format_data(ids, matched_imgs))
return len(ids)
def do_train(table_name, database_path):
detector = Detector()
if not table_name:
table_name = DEFAULT_TABLE
cache = Cache(default_cache_dir)
try:
result_images, object_num = run(detector, database_path)
#print("after detect:", object_num)
vectors, obj_images = get_object_vector(cache, image_encoder,
database_path + "/object")
#print("after detect:", len(vectors), obj_images)
index_client = milvus_client()
status, ok = has_table(index_client, table_name)
if not ok:
print("create table.")
create_table(index_client, table_name=table_name)
print("insert into:", table_name)
# vectors = normaliz_vec(vectors)
status, ids = insert_vectors(index_client, table_name, vectors)
#print(status,ids)
create_index(index_client, table_name)
shutil.rmtree(database_path + "/object")
imgs = os.listdir(database_path)
imgs.sort()
#print("-----imgs", imgs)
k = 0
ids = list(reversed(ids))
#print("ids", ids)
for num in object_num:
for i in range(num):
a = ids.pop()
#print("real;;;;;;;;;",a, imgs[k])
cache[a] = imgs[k]
k += 1
return print("train finished")
except Exception as e:
logging.error(e)
return "Error with {}".format(e)