# -*- encoding: utf-8 -*- # @Author: SWHL # @Contact: liekkaskono@163.com from typing import Tuple import cv2 import numpy as np def reduce_max_side( img: np.ndarray, max_side_len: int = 2000 ) -> Tuple[np.ndarray, float, float]: h, w = img.shape[:2] ratio = 1.0 if max(h, w) > max_side_len: if h > w: ratio = float(max_side_len) / h else: ratio = float(max_side_len) / w resize_h = int(h * ratio) resize_w = int(w * ratio) resize_h = int(round(resize_h / 32) * 32) resize_w = int(round(resize_w / 32) * 32) try: if int(resize_w) <= 0 or int(resize_h) <= 0: raise ResizeImgError("resize_w or resize_h is less than or equal to 0") img = cv2.resize(img, (resize_w, resize_h)) except Exception as exc: raise ResizeImgError() from exc ratio_h = h / resize_h ratio_w = w / resize_w return img, ratio_h, ratio_w def increase_min_side( img: np.ndarray, min_side_len: int = 30 ) -> Tuple[np.ndarray, float, float]: h, w = img.shape[:2] ratio = 1.0 if min(h, w) < min_side_len: if h < w: ratio = float(min_side_len) / h else: ratio = float(min_side_len) / w resize_h = int(h * ratio) resize_w = int(w * ratio) resize_h = int(round(resize_h / 32) * 32) resize_w = int(round(resize_w / 32) * 32) try: if int(resize_w) <= 0 or int(resize_h) <= 0: raise ResizeImgError("resize_w or resize_h is less than or equal to 0") img = cv2.resize(img, (resize_w, resize_h)) except Exception as exc: raise ResizeImgError() from exc ratio_h = h / resize_h ratio_w = w / resize_w return img, ratio_h, ratio_w def add_round_letterbox( img: np.ndarray, padding_tuple: Tuple[int, int, int, int], ) -> np.ndarray: padded_img = cv2.copyMakeBorder( img, padding_tuple[0], padding_tuple[1], padding_tuple[2], padding_tuple[3], cv2.BORDER_CONSTANT, value=(0, 0, 0), ) return padded_img class ResizeImgError(Exception): pass