This dataset contains 2 records. The first record is the annotated dataset. The second record contains a built singularity image containing the code and trained model for predicting on new videos. We generated 1,253 video clips which total 2,637,363 frames. Each video had variable duration, depending upon the grooming prediction length. Annotators were required to provide a "Grooming" or "Not Grooming" annotation for each frame. The annotated dataset is stored in the h5 record and is described as follows: First level grouping is Train/Validation split Second level grouping is by Video Clip Each video contains 5 datasets nframe Number of frames in this video Shape: 1 video Raw Video Shape: nframes x 112 x 112 label Labels for each frame 0 = not grooming, 1 = grooming Shape: nframes mask Information for whether or not annotators agreed 0 = disagree, 1 = agree When annotators disagree, label contains the values from the first person to annotate the frame Shape: nframes nlabelers Number of annotators that have labeled the video clip Shape: 1

Example usage of the trained model: singularity run –nv GroomingInferRelease.sif Input_Movie.avi The input movie must be a 480×480 video and appear visually similar to our training dataset. Since we do not employ distortion augmentation in this model, even slight differences in lighting can cause issues with performance.