Sehara_et_al_2021_RealtimeDLC_DataRepository/01_RawVideos/README.md

Raw Videos for real-time DeepLabCut project

Raw videos, stored in the HDF5 format for the real-time DeepLabCut paper.

Animals

Each directory (except for every10) corresponds to the ID of an animal (all are male C57BL6 adults).

Sessions

train sessions were acquired at 100 Hz without body-part estimation by DeepLabCut. The frames from the videos were used to train deep-neural network models.

Body-part positions were estimated during test sessions, using the model specifically trained for the animal. How body-part positions were evaluated for output generation was noted as the evaluation attribute of the root entry of each HDF file.

the "every10" condition

The "every10" corresponds to the condition where acquisition was run without any animal, and trigger output was flipped after every 10 frames.

This condition was used to measure the timestamp-based inter-frame intervals being acquired with DeepLabCut-based pose estimation.

It is also possible to use it for validation of trigger output latency.