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8096125 | 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 | """2D geometric transformations implemented with OpenCV."""
from __future__ import annotations
import cv2
import numpy as np
from filters.builtin import ensure_rgb
BORDER_MODES = {"constant": cv2.BORDER_CONSTANT, "reflect": cv2.BORDER_REFLECT, "replicate": cv2.BORDER_REPLICATE}
INTERPOLATION = {"nearest": cv2.INTER_NEAREST, "linear": cv2.INTER_LINEAR, "cubic": cv2.INTER_CUBIC, "area": cv2.INTER_AREA}
def translate(image: np.ndarray, x: int = 20, y: int = 20, border: str = "constant") -> tuple[np.ndarray, list[list[float]]]:
img = ensure_rgb(image)
matrix = np.float32([[1, 0, x], [0, 1, y]])
out = cv2.warpAffine(img, matrix, (img.shape[1], img.shape[0]), borderMode=BORDER_MODES.get(border, cv2.BORDER_CONSTANT))
return out, matrix.tolist()
def rotate(image: np.ndarray, angle: float = 30, scale: float = 1.0, center_x: float = 0.5, center_y: float = 0.5, expand: bool = True) -> tuple[np.ndarray, list[list[float]]]:
img = ensure_rgb(image)
h, w = img.shape[:2]
center = (w * center_x, h * center_y)
matrix = cv2.getRotationMatrix2D(center, angle, scale)
out_w, out_h = w, h
if expand:
cos, sin = abs(matrix[0, 0]), abs(matrix[0, 1])
out_w, out_h = int((h * sin) + (w * cos)), int((h * cos) + (w * sin))
matrix[0, 2] += out_w / 2 - center[0]
matrix[1, 2] += out_h / 2 - center[1]
return cv2.warpAffine(img, matrix, (out_w, out_h)), matrix.tolist()
def scale_image(image: np.ndarray, sx: float = 1.2, sy: float = 1.2, interpolation: str = "linear") -> tuple[np.ndarray, list[list[float]]]:
img = ensure_rgb(image)
out = cv2.resize(img, None, fx=sx, fy=sy, interpolation=INTERPOLATION.get(interpolation, cv2.INTER_LINEAR))
return out, [[sx, 0, 0], [0, sy, 0]]
def reflect(image: np.ndarray, mode: str = "horizontal") -> tuple[np.ndarray, list[list[float]]]:
img = ensure_rgb(image)
code = {"horizontal": 1, "vertical": 0, "both": -1}.get(mode, 1)
matrix = {"horizontal": [[-1, 0, img.shape[1]], [0, 1, 0]], "vertical": [[1, 0, 0], [0, -1, img.shape[0]]], "both": [[-1, 0, img.shape[1]], [0, -1, img.shape[0]]]}.get(mode)
return cv2.flip(img, code), matrix
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