idtrackerai

What’s new in idtracker.ai v4

  • Works with Python 3.7.

  • Remove Kivy submodules and stop support for old Kivy GUI.

  • Neural network training is done with Pytorch 1.10.0.

  • Identification images are saved as uint 8.

  • Crossing detector images are the same as the identification images. This saves computing time and makes the process of generating the images faster.

  • Improve data pipeline for the crossing detector.

  • Parallel saving and loading of identification images (only for Linux)

  • Simplify code for connecting blobs from frame to frame.

  • Remove unnecessary execution of the blobs connection algorithm.

  • Background subtraction considers the ROI

  • Allows to save trajectories as csv with the advanced parameter CONVERT_TRAJECTORIES_DICT_TO_CSV_AND_JSON (using the local_settings.py file).

  • Allows to change the output width (and height) of the individual-centered videos with the advanced parameter INDIVIDUAL_VIDEO_WIDTH_HEIGHT (using the local_settings.py file).

  • Horizontal layout for graphical user interface (GUI). This layout can be deactivated using the local_settings.py setting NEW_GUI_LAYOUT=False.

  • Width and height of GUI can be changed using the local_settings.py using the GUI_MINIMUM_HEIGHT and GUI_MINIMUM_WIDTH variables.

  • Add ground truth button to validation GUI.

  • Added “Add setup points” featrue to store landmark points in the video frame that will be stored in the trajectories.npy and trajectories_wo_gaps.npy in the key setup_poitns. Users can use this points to perform behavioural analysis that requires landmarks of the experimental setup.

  • Improved code formatting using the black formatter.

  • Better factorization of the TrackerApi.

  • Some bugs fixed.

  • Better documentation of main idtracker.ai objects (video, blob, list_of_blobs, fragment, list_of_fragments, global_fragment and list_of_global_fragments).

  • Dropped support for MacOS