data_juicer.ops.mapper.video_depth_estimation_mapper module

class data_juicer.ops.mapper.video_depth_estimation_mapper.VideoDepthEstimationMapper(video_depth_model_path: str = 'video_depth_anything_vitb.pth', point_cloud_dir_for_metric: str = '/home/runner/.cache/data_juicer/assets', max_res: int = 1280, torch_dtype: str = 'fp16', if_save_visualization: bool = False, save_visualization_dir: str = '/home/runner/.cache/data_juicer/assets', grayscale: bool = False, *args, **kwargs)

Bases: Mapper

Perform depth estimation on the video.

__init__(video_depth_model_path: str = 'video_depth_anything_vitb.pth', point_cloud_dir_for_metric: str = '/home/runner/.cache/data_juicer/assets', max_res: int = 1280, torch_dtype: str = 'fp16', if_save_visualization: bool = False, save_visualization_dir: str = '/home/runner/.cache/data_juicer/assets', grayscale: bool = False, *args, **kwargs)

Initialization method.

Parameters:

• video_depth_model_path – The path to the Video-Depth-Anything model. If the model is a ‘metric’ model, the code will automatically switch to metric mode, and the user should input the path for storing point clouds.

• point_cloud_dir_for_metric – The path for storing point clouds (for a ‘metric’ model).

• max_res – The maximum resolution threshold for videos; videos exceeding this threshold will be resized.

• torch_dtype – The floating point type used for model inference. Can be one of [‘fp32’, ‘fp16’]

• if_save_visualization – Whether to save visualization results.

• save_visualization_dir – The path for saving visualization results.

• grayscale – If True, the colorful palette will not be applied.

process_single(sample=None, rank=None)

For sample level, sample –> sample

Parameters:

sample – sample to process

Returns:

processed sample