python opencv裁剪数据增强

  

   

    

     

    
    

     

      import glob
     
    
   

    

     

    
    

     

      import random
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      import cv2
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      import numpy as np
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      dir=r'F:\data'
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      files=glob.glob(dir+'/*.jpg')
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      big_count=0
     
    
   

    

     

    
    

     

      file_len=len(files)
     
    
   

    

     

    
    

     

      for file in files:
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

          img_raw = cv2.imread(file)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

          area_o=f"{img_raw.shape[1]*img_raw.shape[0]}_{max(img_raw.shape[1],img_raw.shape[0])}"
     
    
   

    

     

    
    

     
    if img_raw.shape[1]*img_raw.shape[0] > 200*300:
     
    
   

    

     

    
    

     

              x_scale = 224 / max(img_raw.shape[1],img_raw.shape[0])
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

              img_raw = cv2.resize(img_raw, None, fx=x_scale, fy=x_scale, interpolation=cv2.INTER_AREA)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

          cv2.imshow("img_raw", img_raw)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

          img_h,img_w=img_raw.shape[:2]
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

          x_1=random.randint(0, int(img_w*0.05))
     
    
   

    

     

    
    

     

          y_1=random.randint(0, int(img_h*0.05))
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

          x_2=random.randint( int(img_w*0.95),img_w)
     
    
   

    

     

    
    

     

          y_2=random.randint( int(img_h*0.95),img_h)
     
    
   

    

     

    
    

     

          img_crop=img_raw[y_1:y_2,x_1:x_2] #子区域
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

          t_h, t_w = img_crop.shape[:2]
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
    if t_h*t_w>50*200:
     
    
   

    

     

    
    

     

              big_count+=1
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
    print(file_len,big_count)
     
    
   

    

     

    
    

     

          a_w = max(t_w, t_h)
     
    
   

    

     

    
    

     

          a_w = max(a_w,200)
     
    
   

    

     

    
    

     

          img_b = np.zeros((a_w, a_w, 3), dtype=np.uint8)
     
    
   

    

     

    
    

     

          img_b[:t_h, :t_w, :] = img_crop
     
    
   

    

     

    
    

     

          img = cv2.resize(img_b,(128,128))
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

          cv2.imwrite(r'F:\chuli/'+area_o+".jpg",img_b)
     
    
   

    

     

    
    

     
    # cv2.imshow("img_crop", img)
     
    
   

    

     

    
    

     
    # cv2.waitKey()
     
    
  
 

  
 
 

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/125947228