initialize_project.new
logger_config
logger
init_new_project
def init_new_project(project_name: str,
videos: List[str],
poses_estimations: List[str],
source_software: Literal["DeepLabCut", "SLEAP",
"LightningPose"],
working_directory: str = ".",
video_type: str = ".mp4",
fps: int | None = None,
copy_videos: bool = False,
paths_to_pose_nwb_series_data: Optional[str] = None,
config_kwargs: Optional[dict] = None) -> Tuple[str, dict]
Creates a new VAME project with the given parameters. A VAME project is a directory with the following structure:
- project_name/
- data/
- raw/
- session1.mp4
- session1.nc
- session2.mp4
- session2.nc
- ...
- processed/
- session1_processed.nc
- session2_processed.nc
- ...
- raw/
- model/
- pretrained_model/
- results/
- video1/
- video2/
- ...
- states/
- states.json
- config.yaml
- data/
Parameters
- project_name (
str
): Project name. - videos (
List[str]
): List of videos paths to be used in the project. E.g. ['./sample_data/Session001.mp4'] - poses_estimations (
List[str]
): List of pose estimation files paths to be used in the project. E.g. ['./sample_data/pose estimation/Session001.csv'] - source_software (
Literal["DeepLabCut", "SLEAP", "LightningPose"]
): Source software used for pose estimation. - working_directory (
str, optional
): Working directory. Defaults to '.'. - video_type (
str, optional
): Video extension (.mp4 or .avi). Defaults to '.mp4'. - fps (
int, optional
): Sampling rate of the videos. If not passed, it will be estimated from the video file. Defaults to None. - copy_videos (
bool, optional
): If True, the videos will be copied to the project directory. If False, symbolic links will be created instead. Defaults to False. - paths_to_pose_nwb_series_data (
Optional[str], optional
): List of paths to the pose series data in nwb files. Defaults to None. - config_kwargs (
Optional[dict], optional
): Additional configuration parameters. Defaults to None.
Returns
Tuple[str, dict]
: Tuple containing the path to the config file and the config data.