video

def load_video(source: str | torch.Tensor | list, **kwargs) -> torch.Tensor:
    """Load a video as a ``(T, C, H, W)`` float32 tensor in ``[0, 1]``.
Supported *source* types:

* **str / Path** – path to ``.mp4`` / ``.avi`` / ``.gif`` file, or a
  directory of frame images (sorted alphabetically).
* **torch.Tensor** – returned as-is after shape validation.
* **list[PIL.Image]** – stacked into a tensor.
"""
if isinstance(source, torch.Tensor):
    if source.ndim != 4:
        raise ValueError(f"Expected video tensor with 4 dims (T,C,H,W), got {source.ndim}")
    return source.float()

if isinstance(source, list):
    frames = [_pil_to_tensor(img) for img in source]
    return torch.stack(frames)

path = Path(source)
if path.is_dir():
    return _load_frame_dir(path)
return _load_video_file(str(path))</code></pre></details>
fastvideo.eval.io.video.extract_frames
extract_frames(video: torch.Tensor, n_frames: int | None = None) -> torch.Tensor
Uniformly sample n_frames from a (T, C, H, W) video tensor.
Source
def extract_frames(video: torch.Tensor, n_frames: int | None = None) -> torch.Tensor:
    """Uniformly sample *n_frames* from a ``(T, C, H, W)`` video tensor."""
    if n_frames is None or n_frames >= video.shape[0]:
        return video
    indices = torch.linspace(0, video.shape[0] - 1, n_frames).long()
    return video[indices]
fastvideo.eval.io.video.probe_video_fps
probe_video_fps(source: str | Path) -> float | None
Read a path-backed video's native frame rate without decoding frames.
Source
def probe_video_fps(source: str | Path) -> float | None:
    """Read a path-backed video's native frame rate without decoding frames."""
    try:
        import av
    with av.open(str(source)) as container:
        if not container.streams.video:
            return None
        stream = container.streams.video&#91;0&#93;
        rate = stream.average_rate or stream.guessed_rate
        if rate is not None and float(rate) &gt; 0:
            return float(rate)
except (ImportError, OSError, ValueError):
    pass
try:
    from decord import VideoReader, cpu

    rate = float(VideoReader(str(source), ctx=cpu(0)).get_avg_fps())
    return rate if rate &gt; 0 else None
except (ImportError, OSError, RuntimeError, ValueError):
    return None</code></pre></details>