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: