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:
image = plt.imread(f)
ax[i % 2][i // 2].imshow(image)
plt.show()
bem_precision_results = lbp_precision_results = []
bem_precision_results = bem_searcher.precision_recall(bem_features)
lbp_precision_results = lbp_searcher.precision_recall(lbp_features)
print(np.multiply(lbp_precision_results, 100))
fig = plt.figure(figsize=(10, 8))
ax = fig.add_subplot(1, 2, 1)
ax.plot(lbp_precision_results)
ax.set_title("LBP image")
ax.set_xlabel("Number of retrieved images")
ax.set_ylabel("Precision")
ax = fig.add_subplot(1, 2, 2)
ax.plot(bem_precision_results)
ax.set_title("LBP with refinement")
ax.set_xlabel("Number of retrieved images")
ax.set_ylabel("Precision")
