"""Image + video handling. Stills load directly; videos are sampled into frames
(ffmpeg) at the cadence FC sends — so a video becomes a bag of per-frame
instances, each with a timestamp."""
import io
import os
import subprocess
import tempfile

from PIL import Image


def is_video(mime: str) -> bool:
    return bool(mime) and (mime.startswith("video/") or mime in {"image/gif"})


def to_rgb(img: Image.Image) -> Image.Image:
    """RGB, flattening any transparency onto white first. A naive convert('RGB')
    on a palette-with-transparency image (common for character PNGs on a clear
    background) lets PIL guess the transparent pixels — usually black artifacts
    that bleed into the crop + the embedding (and the "should be converted to
    RGBA" warning). Compositing over white gives a clean, consistent background."""
    if img.mode in ("RGBA", "LA", "PA") or (
        img.mode == "P" and "transparency" in img.info
    ):
        img = img.convert("RGBA")
        bg = Image.new("RGBA", img.size, (255, 255, 255, 255))
        return Image.alpha_composite(bg, img).convert("RGB")
    return img.convert("RGB")


def load_image(data: bytes) -> Image.Image:
    return to_rgb(Image.open(io.BytesIO(data)))


def sample_frames(
    data: bytes, interval_seconds: float, max_frames: int
) -> list[tuple[float, Image.Image]]:
    """Extract up to max_frames frames at one-every-interval_seconds via ffmpeg.
    Returns [(timestamp_seconds, frame)]. Empty on failure (caller falls back)."""
    interval = max(0.5, float(interval_seconds or 4.0))
    cap = max(1, int(max_frames or 64))
    with tempfile.TemporaryDirectory() as tmp:
        src = os.path.join(tmp, "in")
        with open(src, "wb") as fh:
            fh.write(data)
        pattern = os.path.join(tmp, "f_%05d.jpg")
        try:
            subprocess.run(
                [
                    "ffmpeg", "-nostdin", "-loglevel", "error", "-i", src,
                    "-vf", f"fps=1/{interval}", "-frames:v", str(cap),
                    "-q:v", "3", pattern,
                ],
                check=True, timeout=600,
            )
        except (subprocess.SubprocessError, FileNotFoundError):
            return []
        out: list[tuple[float, Image.Image]] = []
        names = sorted(n for n in os.listdir(tmp) if n.startswith("f_"))
        for i, name in enumerate(names[:cap]):
            with Image.open(os.path.join(tmp, name)) as im:
                out.append((round(i * interval, 2), to_rgb(im)))
        return out