Python class

OutputVideoContent

`OutputVideoContent`

class max.pipelines.request.OutputVideoContent(*, type='output_video', video_url=None, video_data=None, format=None, frames_per_second=None, num_frames=None, frames=None)

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Bases: BaseModel

Video content generated by the model in output messages.

Parameters:

type (Literal['output_video'])
video_url (str | None)
video_data (str | None)
format (str | None)
frames_per_second (int | None)
num_frames (int | None)
frames (Annotated[ndarray[tuple[Any, ...], dtype[uint8]] | None, SkipJsonSchema()])

`format`

format: str | None

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`frames`

frames: SkipJsonSchema[npt.NDArray[np.uint8] | None]

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`frames_per_second`

frames_per_second: int | None

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`from_numpy_frames()`

classmethod from_numpy_frames(frames, *, frames_per_second=None, format=None)

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Create internal video content from raw frame data.

Parameters:

frames (ndarray[tuple[Any, ...], dtype[uint8]]) – A uint8 array with shape [T, H, W, C] containing raw video frames.
frames_per_second (int | None) – Optional frame rate metadata to attach.
format (str | None) – Optional output format metadata, typically "mp4".

Returns:

An OutputVideoContent instance carrying raw frames for later route-level encoding.

Return type:

OutputVideoContent

`model_config`

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'frozen': True}

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Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

`num_frames`

num_frames: int | None

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`type`

type: Literal['output_video']

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`video_data`

video_data: str | None

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`video_url`

video_url: str | None

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OutputVideoContent​

format​

frames​

frames_per_second​

from_numpy_frames()​

model_config​

num_frames​

type​

video_data​

video_url​