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491e75d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | from __future__ import annotations
import re
from typing import Any
_BOX_PATTERN = re.compile(
r"\[\s*(?P<x_left>-?\d+(?:\.\d+)?)\s*,\s*"
r"(?P<y_top>-?\d+(?:\.\d+)?)\s*,\s*"
r"(?P<x_right>-?\d+(?:\.\d+)?)\s*,\s*"
r"(?P<y_bottom>-?\d+(?:\.\d+)?)\s*\]"
)
_CANONICAL_PATTERN = re.compile(
r"\{\s*(?P<x_left>-?\d+(?:\.\d+)?)\s*,\s*"
r"(?P<y_top>-?\d+(?:\.\d+)?)\s*,\s*"
r"(?P<x_right>-?\d+(?:\.\d+)?)\s*,\s*"
r"(?P<y_bottom>-?\d+(?:\.\d+)?)\s*\|\s*"
r"(?P<angle>-?\d+(?:\.\d+)?)\s*\}"
)
_IMAGE_MARKER = re.compile(r"(?:image|frame)\s*(?P<index>\d+)", re.IGNORECASE)
class BoundingBoxError(ValueError):
pass
def _box(values: dict[str, str], angle: float = 0.0) -> dict[str, float]:
result = {key: float(values[key]) for key in ("x_left", "y_top", "x_right", "y_bottom")}
result["angle"] = angle
if any(value < 0 or value > 100 for key, value in result.items() if key != "angle"):
raise BoundingBoxError("TEOChat bounding-box coordinates must be normalized to [0, 100]")
if result["x_left"] > result["x_right"] or result["y_top"] > result["y_bottom"]:
raise BoundingBoxError("TEOChat bounding-box geometry is invalid")
return result
def _image_index(text: str, start: int, image_count: int) -> int:
prefix = text[max(0, start - 80):start]
markers = list(_IMAGE_MARKER.finditer(prefix))
index = int(markers[-1].group("index")) - 1 if markers else 0
if not 0 <= index < image_count:
raise BoundingBoxError("TEOChat bbox image index is out of range")
return index
def extract_bboxes(text: str) -> list[list[float]]:
"""Backward-compatible extraction of the repository's [x1,y1,x2,y2] format."""
return [
[int(match.group(name)) for name in ("x_left", "y_top", "x_right", "y_bottom")]
for match in _BOX_PATTERN.finditer(text or "")
]
def normalize_bboxes(text: str, image_count: int) -> list[dict[str, Any]]:
"""Convert model bbox text into image-associated canonical evidence."""
if image_count < 1:
raise ValueError("image_count must be positive")
output: list[dict[str, Any]] = []
canonical_matches = list(_CANONICAL_PATTERN.finditer(text or ""))
occupied = [(match.start(), match.end()) for match in canonical_matches]
matches: list[tuple[int, Any, bool]] = [(match.start(), match, True) for match in canonical_matches]
for match in _BOX_PATTERN.finditer(text or ""):
if any(start < match.end() and match.start() < end for start, end in occupied):
continue
matches.append((match.start(), match, False))
for _, match, canonical in sorted(matches, key=lambda item: item[0]):
image_index = _image_index(text, match.start(), image_count)
angle = float(match.group("angle")) if canonical else 0.0
output.append({"image_index": image_index, "box": _box(match.groupdict(), angle)})
return output
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