Hi，Thank you for your such great work! I feels a little bit confused about the training data used in your code. The data orgnization you mentioned in https://github.com/BryanPlummer/cite/tree/master/data_processing_example
is in h5 form right? I don't understand the meaning of <pair identifier> in data['pair'] in the h5 file, I guess the later element in the pair means whether this phrase is the ground truth phrase of the image, beacause in your code, you said we can use the augmented phrase for training, but what the meaning of the first element in the pair? Besides, when you count the ground truth phrase of the image, it seems worry in your code:
you count the num of the ground truth phrase before putting the current gt phrase into list. By the way, how did you generate the augmented phrase? can you explain a little bit about that? Is the result in your paper trained with these augmented phrase?
Hi，Thank you for your such great work! I feels a little bit confused about the training data used in your code. The data orgnization you mentioned in https://github.com/BryanPlummer/cite/tree/master/data_processing_example
is in h5 form right? I don't understand the meaning of <pair identifier> in data['pair'] in the h5 file, I guess the later element in the pair means whether this phrase is the ground truth phrase of the image, beacause in your code, you said we can use the augmented phrase for training, but what the meaning of the first element in the pair? Besides, when you count the ground truth phrase of the image, it seems worry in your code:
you count the num of the ground truth phrase before putting the current gt phrase into list. By the way, how did you generate the augmented phrase? can you explain a little bit about that? Is the result in your paper trained with these augmented phrase?