YannisK commited on
Commit
f1b5b7f
1 Parent(s): 9595159
Files changed (1) hide show
  1. app.py +4 -6
app.py CHANGED
@@ -51,10 +51,10 @@ transform = transforms.Compose([
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  def match(query_feat, pos_feat, LoweRatioTh=0.9):
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  # first perform reciprocal nn
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  dist = torch.cdist(query_feat, pos_feat)
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- print('dist.size',dist.size())
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  best1 = torch.argmin(dist, dim=1)
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  best2 = torch.argmin(dist, dim=0)
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- print('best2.size',best2.size())
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  arange = torch.arange(best2.size(0))
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  reciprocal = best1[best2]==arange
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  # check Lowe ratio test
@@ -84,8 +84,8 @@ def generate_matching_superfeatures(
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  Imagenet_model=False,
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  scale_id=6, threshold=50,
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  random_mode=False, sf_ids=''): #, only_matching=True):
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- print('im1:', im1.size)
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- print('im2:', im2.size)
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  clear_figures()
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  col = plt.get_cmap('tab10')
@@ -159,8 +159,6 @@ def generate_matching_superfeatures(
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  img1rsz[m,n, :] = col_[::-1]
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  img2rsz = np.copy(im2_cv)
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- print('im2:', im2.size)
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- print('img2rsz:', img2rsz.shape)
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  for j, att in enumerate(all_att_bin2):
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  att = cv2.resize(att, im2.size, interpolation=cv2.INTER_NEAREST)
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  mask2d = zip(*np.where(att==255))
 
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  def match(query_feat, pos_feat, LoweRatioTh=0.9):
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  # first perform reciprocal nn
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  dist = torch.cdist(query_feat, pos_feat)
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+ # print('dist.size',dist.size())
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  best1 = torch.argmin(dist, dim=1)
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  best2 = torch.argmin(dist, dim=0)
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+ # print('best2.size',best2.size())
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  arange = torch.arange(best2.size(0))
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  reciprocal = best1[best2]==arange
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  # check Lowe ratio test
 
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  Imagenet_model=False,
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  scale_id=6, threshold=50,
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  random_mode=False, sf_ids=''): #, only_matching=True):
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+ # print('im1:', im1.size)
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+ # print('im2:', im2.size)
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  clear_figures()
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  col = plt.get_cmap('tab10')
 
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  img1rsz[m,n, :] = col_[::-1]
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  img2rsz = np.copy(im2_cv)
 
 
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  for j, att in enumerate(all_att_bin2):
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  att = cv2.resize(att, im2.size, interpolation=cv2.INTER_NEAREST)
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  mask2d = zip(*np.where(att==255))