# load the query image and process it
queryImage = cv2.imread(args["query"])
cv2.imshow("Query", imutils.resize(queryImage, width=320))
queryImage = imutils.resize(queryImage, width=320)
queryImage = cv2.cvtColor(queryImage, cv2.COLOR_BGR2GRAY)
# extract features from the query image and construct a bag-of-visual-words from it
(_, descs) = dad.describe(queryImage)
hist = bovw.describe(descs).tocoo()
# connect to redis and perform the search
redisDB = Redis(host="localhost", port=6379, db=0)
searcher = Searcher(redisDB,
args["bovw_db"],
args["features_db"],
idf=idf,
distanceMetric=distanceMetric)
sr = searcher.search(hist, numResults=20)
print("[INFO] search took: {:.2f}s".format(sr.search_time))
# initialize the results montage
montage = ResultsMontage((240, 320), 5, 20)
# loop over the individual results
for (i, (score, resultID, resultIdx)) in enumerate(sr.results):
# load the result image and display it
print("[RESULT] {result_num}. {result} - {score:.2f}".format(
result_num=i + 1, result=resultID, score=score))
result = cv2.imread("{}/{}".format(args["dataset"], resultID))
montage.addResult(result,