Structured h5 files with the video features and annotations of the SumMe and TVSum datasets are available within the "data" folder. The GoogleNet features of the video frames were extracted by [Ke Zhang](https://github.com/kezhang-cs) and [Wei-Lun Chao] and the h5 files were obtained from [Kaiyang Zhou](https://github.com/KaiyangZhou/pytorch-vsumm-reinforce).
These files have the following structure:
```
/key
/features 2D-array with shape (n_steps, feature-dimension)
/gtscore 1D-array with shape (n_steps), stores ground truth improtance score (used for training, e.g. regression loss)
/user_summary 2D-array with shape (num_users, n_frames), each row is a binary vector (used for test)
/change_points 2D-array with shape (num_segments, 2), each row stores indices of a segment
/n_frame_per_seg 1D-array with shape (num_segments), indicates number of frames in each segment
/n_frames number of frames in original video
/picks positions of subsampled frames in original video
/n_steps number of subsampled frames
/gtsummary 1D-array with shape (n_steps), ground truth summary provided by user (used for training, e.g. maximum likelihood)
/video_name (optional) original video name, only available for SumMe dataset
```
Original videos and annotations for each dataset are also available in the authors' project webpages:
