Scene video class#

class pyneon.video.NeonVideo(video_file: Path, timestamps_file: Path, info_file: Path)#

Bases: VideoCapture

Loaded video file with timestamps.

Parameters:

  • video_file (pathlib.Path) – Path to the video file.

  • timestamps_file (pathlib.Path) – Path to the timestamps file.

  • info_file (pathlib.Path) – Path to the scene camera info file.

timestamps#

Timestamps of the video frames in nanoseconds.

Type:

numpy.ndarray

ts#

Alias for timestamps.

Type:

numpy.ndarray

n_frames#

Number of frames in the video.

Type:

int

fps#

Frames per second of the video.

Type:

float

width#

Width of the video frames in pixels.

Type:

int

height#

Height of the video frames in pixels.

Type:

int

plot_frame(index: int = 0, ax: Axes | None = None, auto_title: bool = True, show: bool = True)#

Plot a frame from the video on a matplotlib axis.

Parameters:

  • index (int) – Index of the frame to plot.

  • ax (matplotlib.axes.Axes or None) – Axis to plot the frame on. If None, a new figure is created. Defaults to None.

  • auto_title (bool) – Whether to automatically set the title of the axis. The automatic title includes the video file name and the frame index. Defaults to True.

Returns:

  • fig (matplotlib.figure.Figure) – Figure object containing the plot.

  • ax (matplotlib.axes.Axes) – Axis object containing the plot.

plot_scanpath_on_video(scanpath: DataFrame, circle_radius: int = 10, line_thickness: int = 2, max_fixations: int = 10, show_video: bool = False, video_output_path: Path | str = 'scanpath.mp4') → None#

Plot scanpath on top of the video frames. The resulting video can be displayed and/or saved.

Parameters:

  • scanpath (pandas.DataFrame) – DataFrame containing the fixations and gaze data.

  • circle_radius (int) – Radius of the fixation circles in pixels. Defaults to 10.

  • line_thickness (int or None) – Thickness of the lines connecting fixations. If None, no lines are drawn. Defaults to 2.

  • max_fixations (int) – Maximum number of fixations to plot per frame. Defaults to 10.

  • show_video (bool) – Whether to display the video with fixations overlaid. Defaults to False.

  • video_output_path (pathlib.Path or str or None) – Path to save the video with fixations overlaid. If None, the video is not saved. Defaults to ‘scanpath.mp4’.

pyneon.video.estimate_scanpath(video: NeonVideo, sync_gaze: NeonGaze, lk_params: dict | None = None) → DataFrame#

Map fixations to video frames using optical flow.

Parameters:

  • video (NeonVideo) – Video object containing the frames.

  • sync_gaze (NeonGaze) – Gaze data synchronized with the video frames.

  • lk_params (dict, optional) – Parameters for the Lucas-Kanade optical flow algorithm.

Returns:

DataFrame containing the scanpath with updated fixation points.

Return type:

pandas.DataFrame