fig, ax = plt.subplots(2, 5, dpi=100)
plt.subplots_adjust(wspace=0.9)
for i in range(10):
with open(filenames[i], 'rb') as f:
image = plt.imread(f)
ax[i % 2][i // 2].imshow(image)
plt.show()
# Set the timer
now = d.now()
current = now.strftime("%H:%M:%S")
print(current)
# describe BEM features and perform the search
bem_features = cd.calculate_bem(query)
bem_searcher = Searcher("bem_value.csv")
bem_results = bem_searcher.search(bem_features)
print(bem_results)
# Plot result images from LBP
filenames = []
for (score, resultID) in bem_results:
filenames.append("Corel/" + resultID)
print(filenames)
fig, ax = plt.subplots(2, 5, dpi=100)
plt.subplots_adjust(wspace=0.7)
for i in range(10):
with open(filenames[i], 'rb') as f:
