--- a
+++ b/usage/plotter.py
@@ -0,0 +1,62 @@
+import matplotlib.pyplot as plt
+import cv2
+import numpy as np
+
+im_path = 'train_15/ref_Training_phase_1_003.png'
+img = np.transpose(cv2.imread(im_path),[1,0,2])
+img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+t_w = img.shape[0]
+w = img.shape[0]//5
+slide = img[4*w:t_w,:,:]
+gt = img[3*w:4*w,:,:]
+prob_map = img[1*w:2*w,:,:]
+prob_map = np.mean(prob_map, axis=2)
+prob_map/=255
+pred = img[2*w:3*w,:,:]
+# raise ValueError
+
+fig, ax = plt.subplots(2, 2, figsize=(24, 24))
+fig.tight_layout()
+im_ = ax[0][0].imshow(slide)
+ax[0][0].set_xticklabels([])
+ax[0][0].set_yticklabels([])
+ax[0][0].set_xticks([])
+ax[0][0].set_yticks([])
+ax[0][0].set_aspect('equal')
+ax[0][0].tick_params(bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off' )
+# ax[0][0].title.set_text("WSI Slide")
+
+gt_ = ax[0][1].imshow(gt,cmap='gray')
+ax[0][1].set_xticklabels([])
+ax[0][1].set_yticklabels([])
+ax[0][1].set_xticks([])
+ax[0][1].set_yticks([])
+ax[0][1].set_aspect('equal')
+ax[0][1].tick_params(bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off' )
+# ax[0][1].title.set_text("Ground Truth")
+
+pred_ = ax[1][1].imshow(pred,cmap='gray')
+ax[1][1].set_xticklabels([])
+ax[1][1].set_yticklabels([])
+ax[1][1].set_xticks([])
+ax[1][1].set_yticks([])
+ax[1][1].set_aspect('equal')
+ax[1][1].tick_params(bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off' )
+# ax[1][1].title.set_text("Ground Truth")
+
+prob_map_ = ax[1][0].imshow(prob_map, cmap=plt.cm.jet)
+ax[1][0].set_xticklabels([])
+ax[1][0].set_yticklabels([])
+ax[1][0].set_xticks([])
+ax[1][0].set_yticks([])
+ax[1][0].set_aspect('equal')
+ax[1][0].tick_params(bottom='off', top='off', labelbottom='off', right='off', left='off', labelleft='off' )
+# ax[1][0].title.set_text("Probability Map")
+
+cax = fig.add_axes([ax[1][0].get_position().x1 + 0.01,
+          ax[1][0].get_position().y0,
+          0.01,
+          ax[1][0].get_position().y1-ax[1][0].get_position().y0])
+fig.colorbar(prob_map_, cax=cax)
+
+plt.savefig('characteristic-plots/im2.png',bbox_inches = 'tight',pad_inches = 0.1)