Apply image cropping in matching result visualization

match_two.py

@@ -151,6 +151,10 @@ def match_two(model, device, config, im_one, im_two, plot_save_path):
             tqdm.write('====> Plotting Local Features and save them to ' + str(join(plot_save_path, 'patchMatchings.png')))
 
         # using cv2 for their in-built keypoint correspondence plotting tools
+        if crop_roi is not None:
+            top, left, bottom, right = crop_roi
+            im_one = im_one[top:bottom,left:right]
+            im_two = im_two[top:bottom,left:right]
         cv_im_one = cv2.resize(im_one, (int(config['feature_extract']['imageresizeW']), int(config['feature_extract']['imageresizeH'])))
         cv_im_two = cv2.resize(im_two, (int(config['feature_extract']['imageresizeW']), int(config['feature_extract']['imageresizeH'])))
         # cv2 resize slightly different from torch, but for visualisation only not a big problem