61 lines
1.7 KiB
Python
61 lines
1.7 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any
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@dataclass
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class MetricResult:
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"""Standard result container returned by all metrics.
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``score`` is ``None`` when the metric was skipped (e.g. missing
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required input). Check ``details["skipped"]`` for the reason.
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"""
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name: str
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score: float | None
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details: dict[str, Any] = field(default_factory=dict)
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class EvalResults(list):
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"""Return type for :meth:`Evaluator.evaluate` with ``samples=...``.
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Behaves like a ``list[dict[str, MetricResult]]`` — one dict per
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input sample, in input order — so existing iteration and indexing
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keeps working. The ``corpus`` attribute carries set-metric results
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(FAD, IS, …) that are properties of the whole input set, not of
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any individual sample. Empty dict when no set metric ran.
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"""
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def __init__(
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self,
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samples: list[dict[str, MetricResult]] | None = None,
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corpus: dict[str, MetricResult] | None = None,
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) -> None:
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super().__init__(samples or [])
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self.corpus: dict[str, MetricResult] = corpus or {}
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@dataclass
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class Video:
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"""Path-backed media handle. The :class:`VideoPool` populates
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``frames`` (and optionally ``audio``) before the metric loop sees
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the sample.
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"""
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source: Any
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fps: float | None = None
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frames: Any = None
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audio: Any = None
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audio_sr: int | None = None
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def has_frames(self) -> bool:
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return self.frames is not None
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def has_audio(self) -> bool:
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return self.audio is not None
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def __post_init__(self) -> None:
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if isinstance(self.source, Path):
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self.source = str(self.source)
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