elif args["class"] == "gabor":
params = {
"theta": 4,
"frequency": (0, 1, 0.5, 0.8),
"sigma": (1, 3),
"n_slice": 2
}
gd = GaborDescriptor(params)
gaborKernels = gd.kernels()
query = cv2.imread(args["query"])
features = gd.gaborHistogram(query, gaborKernels)
searcher = Searcher("gabor/index.csv")
results = searcher._gsearch(features)
elif args["class"] == "hog":
hog = HOGDescriptor()
query = cv2.imread(args["query"])
features = hog.describe(query)
searcher = Searcher("hog/index.csv")
results = searcher.search(features)
myWindow = cv2.resize(query, (960, 960))
cv2.imshow("query", myWindow)
for (score, resultId) in results:
print(score)
