技術標籤：python學習

由於UCMD資料集較少，只有2100張，使用旋轉資料增強，此程式碼用於增強2100張。

import tensorflow as tf
import os
 
def trans(img, img_data, sav):
    
   
    rotate_90 = tf.image.rot90(img_data, k=1)
    encoded_image_r9 = tf.image.encode_jpeg(rotate_90)

    with tf.Session() as sess:
       
        r9 = sess.run(encoded_image_r9)
 

        img_classes=img.split('.')[0]
        houzhui=img.split('.')[1]
        img_rename=img_classes+'_aug90.'+houzhui
        f = tf.gfile.GFile(os.path.join(sav, img_rename), 'wb')
        f.write(r9)
        
       
class_dict = {'agricultural': 0,
                  'airplane': 1,
                  'buildings'
 
: 4,
                  'chaparral': 5,
                  'denseresidential': 6,
                  'forest': 7,
                  'freeway': 8,
                  'golfcourse': 9,
                  'harbor': 10,
                  'intersection': 11,
                  'mediumresidential': 12,
                  'mobilehomepark'
 
: 13,
                  'overpass': 14,
                  'parkinglot': 15,
                  'river': 16,
                  'runway': 17,
                  'sparseresidential': 18,
                  'tenniscourt': 20}
for item in class_dict.keys():
       img_dir='/Data/yyxx/shaoliyuan/MHCLN-master/UCMD/UCMerced_LandUse/Images/'+item   
       save_dir='/Data/yyxx/shaoliyuan/MHCLN-master/UCMD/UCMerced_LandUse/Images/'+item  
       img_list=os.listdir(img_dir)
       for img in img_list:
           img_path=os.path.join(img_dir,img)
           print(img_path)
           img_raw_data = tf.gfile.FastGFile(img_path, 'rb').read()
           img_data = tf.image.decode_jpeg(img_raw_data)
           trans(img, img_data, save_dir)