bvandeusen
e8d3400d22
The trunk of both crop jobs — CCIP figure-crops and SigLIP concept-crops call the SAME crop_region(): normalized-bbox crop with optional context padding, edge-clamping, and the lower-bound size floor (max of a fraction-of-short-side and an absolute pixel floor) below which a region is too small to embed and returns None. Only the proposer (where) and embedder (what) differ; the crop is shared. Pure Pillow — importable + testable anywhere (the GPU agent imports it for the crop step). Unit-lane tests (no DB): region pixels, floor rejection, edge clamp, pad expansion, out-size resize. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
74 lines
2.7 KiB
Python
74 lines
2.7 KiB
Python
"""Shared crop primitive for the region/crop pipeline (#114).
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One model- and transport-agnostic function sits at the trunk of both crop jobs:
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- CCIP characters: a face/figure detector proposes regions → crop → CCIP-embed.
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- SigLIP concepts: head-guided / saliency proposes regions → crop → SigLIP-embed.
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Only the PROPOSER (where to crop) and the EMBEDDER (what to run) differ; the crop
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itself — including the lower-bound size floor below which a region is too small to
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embed reliably — is identical, so it lives here and both jobs call it.
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The actual detector + embedders run in the GPU agent; this is pure Pillow so it's
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importable + testable anywhere (and the agent imports it for the crop step).
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"""
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from __future__ import annotations
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from PIL import Image
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# Size floor: a region must be at least this big on its SHORTER edge to be worth
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# embedding — a smaller crop is a blurry upscale carrying little real signal, and
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# unbounded tiny crops would explode the bag. Expressed as BOTH a fraction of the
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# image's short side and an absolute pixel floor; the larger of the two wins.
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MIN_CROP_FRACTION = 0.10
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MIN_CROP_PX = 64
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def _to_pixels(bbox: tuple[float, float, float, float], w: int, h: int):
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"""Normalized (x, y, w, h) in [0,1] → pixel (x, y, w, h)."""
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x, y, bw, bh = bbox
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return x * w, y * h, bw * w, bh * h
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def crop_region(
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img: Image.Image,
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bbox: tuple[float, float, float, float],
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*,
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pad: float = 0.0,
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min_fraction: float = MIN_CROP_FRACTION,
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min_px: int = MIN_CROP_PX,
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out_size: int | None = None,
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) -> Image.Image | None:
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"""Crop a NORMALIZED bbox (x, y, w, h in [0,1]) from img.
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- pad: grow the box by this fraction on each side (e.g. 0.15 = +15% context),
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clamped to the image bounds.
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- Returns None when the resulting region is below the size floor (too small to
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embed reliably) — the caller skips embedding it.
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- out_size: if given, resize the crop to out_size×out_size; otherwise return
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the raw crop and let the embedder do its own preprocessing.
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"""
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iw, ih = img.size
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px, py, pw, ph = _to_pixels(bbox, iw, ih)
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if pad:
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px -= pw * pad / 2.0
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py -= ph * pad / 2.0
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pw *= (1.0 + pad)
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ph *= (1.0 + pad)
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left = max(0, int(round(px)))
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top = max(0, int(round(py)))
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right = min(iw, int(round(px + pw)))
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bottom = min(ih, int(round(py + ph)))
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if right <= left or bottom <= top:
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return None
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floor = max(min_px, int(min_fraction * min(iw, ih)))
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if min(right - left, bottom - top) < floor:
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return None
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crop = img.crop((left, top, right, bottom)).convert("RGB")
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if out_size:
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crop = crop.resize((out_size, out_size))
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return crop
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