--- title: types ---

fastvideo.eval.types.MetricResult

MetricResult(name: str, score: float | None, details: dict[str, Any] = dict())

Standard result container returned by all metrics.

score is None when the metric was skipped (e.g. missing required input). Check details["skipped"] for the reason.

Source
@dataclass
class MetricResult:
    """Standard result container returned by all metrics.

    ``score`` is ``None`` when the metric was skipped (e.g. missing
    required input).  Check ``details["skipped"]`` for the reason.
    """
    name: str
    score: float | None
    details: dict[str, Any] = field(default_factory=dict)

fastvideo.eval.types.EvalResults

EvalResults(samples: list[dict[str, MetricResult]] | None = None, corpus: dict[str, MetricResult] | None = None)

Return type for :meth:Evaluator.evaluate with samples=....

Behaves like a list[dict[str, MetricResult]] — one dict per input sample, in input order — so existing iteration and indexing keeps working. The corpus attribute carries set-metric results (FAD, IS, …) that are properties of the whole input set, not of any individual sample. Empty dict when no set metric ran.

Source
class EvalResults(list):
    """Return type for :meth:`Evaluator.evaluate` with ``samples=...``.

    Behaves like a ``list[dict[str, MetricResult]]`` — one dict per
    input sample, in input order — so existing iteration and indexing
    keeps working. The ``corpus`` attribute carries set-metric results
    (FAD, IS, …) that are properties of the whole input set, not of
    any individual sample. Empty dict when no set metric ran.
    """

    def __init__(
        self,
        samples: list[dict[str, MetricResult]] | None = None,
        corpus: dict[str, MetricResult] | None = None,
    ) -> None:
        super().__init__(samples or [])
        self.corpus: dict[str, MetricResult] = corpus or {}

fastvideo.eval.types.Video

Video(source: Any, fps: float | None = None, frames: Any = None, audio: Any = None, audio_sr: int | None = None)

Path-backed media handle. The :class:VideoPool populates frames (and optionally audio) before the metric loop sees the sample.

Source
@dataclass
class Video:
    """Path-backed media handle. The :class:`VideoPool` populates
    ``frames`` (and optionally ``audio``) before the metric loop sees
    the sample.
    """

    source: Any
    fps: float | None = None
    frames: Any = None
    audio: Any = None
    audio_sr: int | None = None

    def has_frames(self) -> bool:
        return self.frames is not None

    def has_audio(self) -> bool:
        return self.audio is not None

    def __post_init__(self) -> None:
        if isinstance(self.source, Path):
            self.source = str(self.source)

fastvideo.eval.types.Video.has_frames

has_frames() -> bool
Source
def has_frames(self) -> bool:
    return self.frames is not None

fastvideo.eval.types.Video.has_audio

has_audio() -> bool
Source
def has_audio(self) -> bool:
    return self.audio is not None