添加二维码处理能力

tool/cv.py

@@ -0,0 +1,146 @@
+"""二维码检测与裁剪工具。"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from pathlib import Path
+
+import cv2
+import numpy as np
+
+
+@dataclass
+class QrRegion:
+    """单个二维码区域。"""
+
+    points: tuple[tuple[int, int], ...]
+    crop: np.ndarray | None = None
+
+
+@dataclass
+class QrDetectResult:
+    """二维码检测结果。"""
+
+    has_qr: bool
+    items: list[QrRegion]
+
+
+def _load_image(image: bytes | np.ndarray | str | Path) -> np.ndarray:
+    """把输入转成 BGR 图像。"""
+    if isinstance(image, np.ndarray):
+        if image.ndim == 2:
+            return cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
+        return image.copy()
+
+    if isinstance(image, (str, Path)):
+        data = Path(image).read_bytes()
+    else:
+        data = image
+
+    arr = np.frombuffer(data, dtype=np.uint8)
+    img = cv2.imdecode(arr, cv2.IMREAD_COLOR)
+    if img is None:
+        raise ValueError("Failed to decode image data.")
+    return img
+
+
+def _order_points(points: np.ndarray) -> np.ndarray:
+    """把四个角点整理成左上、右上、右下、左下。"""
+    pts = np.asarray(points, dtype=np.float32).reshape(4, 2)
+    rect = np.zeros((4, 2), dtype=np.float32)
+
+    s = pts.sum(axis=1)
+    diff = np.diff(pts, axis=1)
+
+    rect[0] = pts[np.argmin(s)]
+    rect[2] = pts[np.argmax(s)]
+    rect[1] = pts[np.argmin(diff)]
+    rect[3] = pts[np.argmax(diff)]
+    return rect
+
+
+def _warp_qr_image(img: np.ndarray, points: np.ndarray) -> np.ndarray:
+    """按四边形点做透视矫正，截取二维码区域。"""
+    rect = _order_points(points)
+    (tl, tr, br, bl) = rect
+
+    width_a = np.linalg.norm(br - bl)
+    width_b = np.linalg.norm(tr - tl)
+    height_a = np.linalg.norm(tr - br)
+    height_b = np.linalg.norm(tl - bl)
+
+    width = max(int(round(max(width_a, width_b))), 1)
+    height = max(int(round(max(height_a, height_b))), 1)
+
+    dst = np.array(
+        [
+            [0, 0],
+            [width - 1, 0],
+            [width - 1, height - 1],
+            [0, height - 1],
+        ],
+        dtype=np.float32,
+    )
+
+    matrix = cv2.getPerspectiveTransform(rect, dst)
+    return cv2.warpPerspective(img, matrix, (width, height))
+
+
+def _normalize_points(points: np.ndarray | None) -> list[tuple[tuple[int, int], ...]]:
+    if points is None:
+        return []
+
+    arr = np.asarray(points)
+    if arr.ndim == 2 and arr.shape == (4, 2):
+        arr = arr[None, ...]
+    elif arr.ndim == 3 and arr.shape[-2:] == (4, 2):
+        pass
+    else:
+        return []
+
+    result: list[tuple[tuple[int, int], ...]] = []
+    for item in arr:
+        quad = tuple((int(round(x)), int(round(y))) for x, y in item)
+        result.append(quad)
+    return result
+
+
+def _detect_points(img: np.ndarray) -> list[tuple[tuple[int, int], ...]]:
+    detector = cv2.QRCodeDetector()
+
+    if hasattr(detector, "detectMulti"):
+        ok, points = detector.detectMulti(img)
+        if ok:
+            normalized_points = _normalize_points(points)
+            if normalized_points:
+                return normalized_points
+
+    ok, points = detector.detect(img)
+    if ok:
+        normalized_points = _normalize_points(points)
+        if normalized_points:
+            return normalized_points
+
+    return []
+
+
+def scan_qr(image: bytes | np.ndarray | str | Path) -> QrDetectResult:
+    """扫描图片中是否存在二维码，并返回二维码区域。"""
+    img = _load_image(image)
+    points_list = _detect_points(img)
+
+    items = [
+        QrRegion(points=points, crop=_warp_qr_image(img, np.array(points, dtype=np.float32)))
+        for points in points_list
+    ]
+    return QrDetectResult(has_qr=bool(items), items=items)
+
+
+def has_qr(image: bytes | np.ndarray | str | Path) -> bool:
+    """判断图片里有没有二维码。"""
+    return scan_qr(image).has_qr
+
+
+def crop_qr(image: bytes | np.ndarray | str | Path) -> list[np.ndarray]:
+    """裁剪出图片中的二维码区域。"""
+    return [item.crop for item in scan_qr(image).items if item.crop is not None]