UCMD数据集旋转数据增强

由于UCMD数据集较少，只有2100张，使用旋转数据增强，此代码用于增强2100张。

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)