edits

app.py

@@ -89,14 +89,7 @@ col = plt.get_cmap('tab10')
 def generate_matching_superfeatures(im1, im2, scale_id=6, threshold=50, sf_ids='', only_matching=True):
     print('im1:', im1.size)
     print('im2:', im2.size)
-    # which sf 
-    sf_idx_ = [55, 14, 5, 4, 52, 57, 40, 9]
-    if sf_ids.lower().startswith('r'):
-        n_sf_ids = int(sf_ids[1:])
-        sf_idx_ = np.random.randint(256, size=n_sf_ids)
-    elif sf_ids != '':
-        sf_idx_ = map(int, sf_ids.strip().split(','))
-        
+
 
     # dataset_ = ImgDataset(images=[im1, im2], imsize=1024)
     # loader = torch.utils.data.DataLoader(dataset_, shuffle=False, pin_memory=True)
@@ -120,8 +113,8 @@ def generate_matching_superfeatures(im1, im2, scale_id=6, threshold=50, sf_ids='
         attns2 = output2[1][0]
         strenghts2 = output2[2][0]
 
-        feats1n = F.normalize(torch.squeeze(feats1), dim=1)
-        feats2n = F.normalize(torch.squeeze(feats2), dim=1)
+        feats1n = F.normalize(torch.t(torch.squeeze(feats1)), dim=1)
+        feats2n = F.normalize(torch.t(torch.squeeze(feats2)), dim=1)
         print('feats1n.shape', feats1n.shape)
         ind_match = match(feats1n, feats2n)
         print('ind', ind_match)
@@ -139,7 +132,20 @@ def generate_matching_superfeatures(im1, im2, scale_id=6, threshold=50, sf_ids='
     print(attns1.shape, attns2.shape)
     print(strenghts1.shape, strenghts2.shape)
     
-    # if only_matching:
+    # which sf 
+    sf_idx_ = [55, 14, 5, 4, 52, 57, 40, 9]
+    if sf_ids.lower().startswith('r'):
+        n_sf_ids = int(sf_ids[1:])
+        sf_idx_ = np.random.randint(256, size=n_sf_ids)
+    elif sf_ids != '':
+        sf_idx_ = map(int, sf_ids.strip().split(','))
+        
+    if only_matching:
+        sf_idx_ = [i for i in sf_idx_ if i in list(ind_match)]
+
+
+
+
 
     # Store all binary SF att maps to show them all at once in the end
     all_att_bin1 = []