# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import cv2 import numpy as np class LetterBoxResize(object): def __init__(self, target_size): """ Resize image to target size, convert normalized xywh to pixel xyxy format ([x_center, y_center, width, height] -> [x0, y0, x1, y1]). Args: target_size (int|list): image target size. """ super(LetterBoxResize, self).__init__() if isinstance(target_size, int): target_size = [target_size, target_size] self.target_size = target_size def letterbox(self, img, height, width, color=(127.5, 127.5, 127.5)): # letterbox: resize a rectangular image to a padded rectangular shape = img.shape[:2] # [height, width] ratio_h = float(height) / shape[0] ratio_w = float(width) / shape[1] ratio = min(ratio_h, ratio_w) new_shape = (round(shape[1] * ratio), round(shape[0] * ratio)) # [width, height] padw = (width - new_shape[0]) / 2 padh = (height - new_shape[1]) / 2 top, bottom = round(padh - 0.1), round(padh + 0.1) left, right = round(padw - 0.1), round(padw + 0.1) img = cv2.resize( img, new_shape, interpolation=cv2.INTER_AREA) # resized, no border img = cv2.copyMakeBorder( img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=color) # padded rectangular return img, ratio, padw, padh def __call__(self, im, im_info): """ Args: im (np.ndarray): image (np.ndarray) im_info (dict): info of image Returns: im (np.ndarray): processed image (np.ndarray) im_info (dict): info of processed image """ assert len(self.target_size) == 2 assert self.target_size[0] > 0 and self.target_size[1] > 0 height, width = self.target_size h, w = im.shape[:2] im, ratio, padw, padh = self.letterbox(im, height=height, width=width) new_shape = [round(h * ratio), round(w * ratio)] im_info['im_shape'] = np.array(new_shape, dtype=np.float32) im_info['scale_factor'] = np.array([ratio, ratio], dtype=np.float32) return im, im_info