数据裁剪增强

裁剪后的相交面积与boxes面积之比：

      def matrix_iof(a, b):
         """
       return iof of a and b, numpy version for data augenmentation
       """
          lt = np.maximum(a[:, np.newaxis, :2], b[:, :2])
          rb = np.minimum(a[:, np.newaxis, 2:], b[:, 2:])
          area_i = np.prod(rb - lt, axis=2) * (lt < rb).all(axis=2)
          area_a = np.prod(a[:, 2:] - a[:, :2], axis=1)
         return area_i / np.maximum(area_a[:, np.newaxis], 1)
  
 

 flag = (value >= 0.7)

data_argment.py：

      import cv2
      import numpy as np
      import random
      from utils.box_utils import matrix_iof
      def _crop(image, boxes, labels, img_size):
         #随意裁剪，裁剪到最后resize，会有放大效果，不会缩小，小目标检测无帮助
          height, width, _ = image.shape
          pad_image_flag = True
         if boxes[0][3] == 0 or boxes[0][2] - boxes[0][0] == 0 or boxes[0][3] - boxes[0][1] 
  
 

文章来源: blog.csdn.net，作者：AI视觉网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/108212925