bvandeusen
3abbe58450
A naive convert('RGB') on a palette-with-transparency image (common: character
PNGs on a clear background) lets PIL guess the transparent pixels — black-ish
artifacts that bleed into the crop + the CCIP embedding (and the "should be
converted to RGBA" warning). to_rgb() composites over white first for a clean,
consistent background; used by both stills and video frames.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
64 lines
2.5 KiB
Python
64 lines
2.5 KiB
Python
"""Image + video handling. Stills load directly; videos are sampled into frames
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(ffmpeg) at the cadence FC sends — so a video becomes a bag of per-frame
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instances, each with a timestamp."""
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import io
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import os
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import subprocess
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import tempfile
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from PIL import Image
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def is_video(mime: str) -> bool:
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return bool(mime) and (mime.startswith("video/") or mime in {"image/gif"})
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def to_rgb(img: Image.Image) -> Image.Image:
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"""RGB, flattening any transparency onto white first. A naive convert('RGB')
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on a palette-with-transparency image (common for character PNGs on a clear
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background) lets PIL guess the transparent pixels — usually black artifacts
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that bleed into the crop + the embedding (and the "should be converted to
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RGBA" warning). Compositing over white gives a clean, consistent background."""
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if img.mode in ("RGBA", "LA", "PA") or (
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img.mode == "P" and "transparency" in img.info
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):
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img = img.convert("RGBA")
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bg = Image.new("RGBA", img.size, (255, 255, 255, 255))
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return Image.alpha_composite(bg, img).convert("RGB")
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return img.convert("RGB")
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def load_image(data: bytes) -> Image.Image:
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return to_rgb(Image.open(io.BytesIO(data)))
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def sample_frames(
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data: bytes, interval_seconds: float, max_frames: int
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) -> list[tuple[float, Image.Image]]:
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"""Extract up to max_frames frames at one-every-interval_seconds via ffmpeg.
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Returns [(timestamp_seconds, frame)]. Empty on failure (caller falls back)."""
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interval = max(0.5, float(interval_seconds or 4.0))
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cap = max(1, int(max_frames or 64))
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with tempfile.TemporaryDirectory() as tmp:
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src = os.path.join(tmp, "in")
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with open(src, "wb") as fh:
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fh.write(data)
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pattern = os.path.join(tmp, "f_%05d.jpg")
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try:
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subprocess.run(
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[
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"ffmpeg", "-nostdin", "-loglevel", "error", "-i", src,
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"-vf", f"fps=1/{interval}", "-frames:v", str(cap),
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"-q:v", "3", pattern,
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],
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check=True, timeout=600,
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)
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except (subprocess.SubprocessError, FileNotFoundError):
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return []
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out: list[tuple[float, Image.Image]] = []
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names = sorted(n for n in os.listdir(tmp) if n.startswith("f_"))
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for i, name in enumerate(names[:cap]):
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with Image.open(os.path.join(tmp, name)) as im:
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out.append((round(i * interval, 2), to_rgb(im)))
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return out
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