| # Boolean masks of the UBnormal Human-Related subset | |
| The folders `testing` and `validating` contain the boolean masks for the test set and the validation set, respectively. | |
| Within each folder, a `hr_mask.npy` is provided, which contains the masks of the clips concatenated by lexicographic order, i.e. in the same order as their names are listed in the folder. | |
| The folders `{testing, validating}/test_frame_mask` contain the masks for each clip as separated Numpy files. Values within the masks are boolean such that | |
| ``` | |
| mask[i] = True if the frame should be kept | |
| mask[i] = False otherwise | |
| ``` | |
| For each set, a `stats.json` file shows the total number of frames in the set, the number of discarded frames and the percentage of discarded frames; the same information is also reported for each clip. | |
| To use the HR mask, add in the evaluation code the following: | |
| ```python | |
| import numpy as np | |
| HR_UBNORMAL_MASK = np.load('data/UBnormal/hr_bool_masks/testing/hr_mask.npy') | |
| ``` | |
| if the clips in the evaluation are **loaded and appear in the code in the same order as their names are sorted in the folder**, otherwise | |
| ```python | |
| import numpy as np | |
| # example for the clip 001_0100 | |
| HR_UBNORMAL_MASK_001_0100 = np.load('data/UBnormal/hr_bool_masks/testing/test_frame_mask/001_0100.npy') | |
| ``` | |
| for each clip. |