Some question about relation_file, attribute_file and gv_feat_file about COCO

[WangLanxiao]

Thank you for your contribution. I read the datacode about COCO carefully. I have a little confused.
As for ext_data, how can I get these data ? Looking forward to your reply.
ext_data = {
"relation": _load_pkl_file(self.relation_file),
"attribute": _load_pkl_file(self.attribute_file),
"gv_feat": _load_pkl_file(self.gv_feat_file)
}

[willow-hu]

Came across the same question, too.
Guess that they are parts of features extracted by bottom-up attention, but I don't know how to obtain the data with the required format.
Looking forward ur reply, thx!

[YehLi]

Thank you for your contribution. I read the datacode about COCO carefully. I have a little confused. As for ext_data, how can I get these data ? Looking forward to your reply. ext_data = { "relation": _load_pkl_file(self.relation_file), "attribute": _load_pkl_file(self.attribute_file), "gv_feat": _load_pkl_file(self.gv_feat_file) }

These files can be downloaded from https://drive.google.com/drive/folders/1FQeX7bPI4y_XbpikNy6yYZ_hFMebEtmW?usp=sharing

[YehLi]

Came across the same question, too. Guess that they are parts of features extracted by bottom-up attention, but I don't know how to obtain the data with the required format. Looking forward ur reply, thx!

The relation file stores the visual relationship among the bottom-up regions for GCN-LSTM. The attribute and gv_feat are the features for LSTM-A. The attribute feature can be extracted by https://github.com/s-gupta/visual-concepts.git (ResNet-101). The gv_feat feature is the output of pool5 layer in ResNet-101.

[WangLanxiao]

Thanks for your reply~

[willow-hu]

Came across the same question, too. Guess that they are parts of features extracted by bottom-up attention, but I don't know how to obtain the data with the required format. Looking forward ur reply, thx!

The relation file stores the visual relationship among the bottom-up regions for GCN-LSTM. The attribute and gv_feat are the features for LSTM-A. The attribute feature can be extracted by https://github.com/s-gupta/visual-concepts.git (ResNet-101). The gv_feat feature is the output of pool5 layer in ResNet-101.

Thx! It's more clear now!

[jianjieluo]

Closed due to inactivity.