edits

app.py

@@ -30,11 +30,11 @@ net.load_state_dict(state['state_dict'])
 
 
 # ---------------------------------------
-# transform = transforms.Compose([
-#         transforms.Resize(1024),
-#         transforms.ToTensor(), 
-#         transforms.Normalize(**dict(zip(["mean", "std"], net.runtime['mean_std'])))
-#         ])
+transform = transforms.Compose([
+        transforms.Resize(1024),
+        transforms.ToTensor(), 
+        transforms.Normalize(**dict(zip(["mean", "std"], net.runtime['mean_std'])))
+        ])
 # ---------------------------------------
 
 class ImgDataset(data.Dataset):
@@ -88,24 +88,24 @@ def generate_matching_superfeatures(im1, im2, scale_id=6, threshold=50, sf_ids='
 
     # extract features
     with torch.no_grad():
-        # output1 = net.get_superfeatures(im1_tensor.to(device), scales=[scales[scale_id]])
-        # feats1 = output1[0][0]
-        # attns1 = output1[1][0]
-        # strenghts1 = output1[2][0]
-
-        # output2 = net.get_superfeatures(im2_tensor.to(device), scales=[scales[scale_id]])
-        # feats2 = output2[0][0]
-        # attns2 = output2[1][0]
-        # strenghts2 = output2[2][0]
-        outputs = []
-        for im_tensor in loader:
-            outputs.append(net.get_superfeatures(im_tensor.to(device), scales=[scales[scale_id]]))
-        feats1 = outputs[0][0][0]
-        attns1 = outputs[0][1][0]
-        strenghts1 = outputs[0][2][0]
-        feats2 = outputs[1][0][0]
-        attns2 = outputs[1][1][0]
-        strenghts2 = outputs[1][2][0]
+        output1 = net.get_superfeatures(im1_tensor.to(device), scales=[scales[scale_id]])
+        feats1 = output1[0][0]
+        attns1 = output1[1][0]
+        strenghts1 = output1[2][0]
+
+        output2 = net.get_superfeatures(im2_tensor.to(device), scales=[scales[scale_id]])
+        feats2 = output2[0][0]
+        attns2 = output2[1][0]
+        strenghts2 = output2[2][0]
+        # outputs = []
+        # for im_tensor in loader:
+        #     outputs.append(net.get_superfeatures(im_tensor.to(device), scales=[scales[scale_id]]))
+        # feats1 = outputs[0][0][0]
+        # attns1 = outputs[0][1][0]
+        # strenghts1 = outputs[0][2][0]
+        # feats2 = outputs[1][0][0]
+        # attns2 = outputs[1][1][0]
+        # strenghts2 = outputs[1][2][0]
     print(feats1.shape, feats2.shape)
     print(attns1.shape, attns2.shape)
     print(strenghts1.shape, strenghts2.shape)