Output structure#

Idtracker.ai will generate a session_[SESSION_NAME] folder in the same directory where the input videos are (or in the --output_dir path if specified, see Output). The session folder may be have the following structure:

Note

The content of the session folder may change depending on the necessities of each session. Also, --data_policy can remove some of the data after finishing a successful tracking (see Output).

idtracker.ai session’s output structure#
session_[SESSION_NAME]
├─ accumulation_*
│  └─ ...
├─ crossings_detector
│  └─ ...
├─ identification_images
│  └─ id_images_*.hdf5
├─ preprocessing
│  ├─ list_of_blobs.pickle
│  └─ list_of_fragments.pickle
├─ segmentation_data
│  └─ episode_images_*.hdf5
├─ trajectories
│  ├─ trajectories.npy
│  └─ trajectories_wo_gaps.npy
├─ video_object.json
└─ idtrackerai.log

The trajectory files are the ones highlighted above, they contain the most valuable data for the end user, the position of every animal in every video frame. See how to read them in Trajectory files.

In the session folder there’s a copy of the session log idtrackerai.log made at the end of the process (successful or not). This file contains information of the entire tracking process and is essential to debug and understand idtracker.ai (see Tracking log).

The majority of the generated data is a byproduct of the tracking process and it is not meant to be read or used by the end user. Still, an intuition of the data content can be read as:

  • accumulation_* contains the identification network model and parameters. It can be used to match identities with other sessions with Idmatcher.ai.

  • crossings_detector contains the individual/crossing classification network model and parameters.

  • identification_images contains the images used for identification. This is, an image for every animal and every frame on the video.

  • preprocessing contains the blobs, fragments and global fragments objects (in Python pickle format). Advanced users can dive into these objects to gather some extra information about the tracking. Also, the ROI and the computed background are saved here.

  • segmentation_data contains the temporal image used to generate the final identification images.

  • video_object.json contains basic properties of the video and the session in human readable .json format.