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