python 判断一个文件或者文件夹存不存在

f = r'/mnt/Data/dd/deeplearning/dataset/data/Tfrecords'
# f = open(f)
print(os.path.exists(f))
True就是存在，然后一层层地判断

读取文件的绝对路径

path=os.path.abspath(os.path.join(current,os.path.pardir,'dataset/data'))
加入abspath以后输出为
/mnt/Data/aa/deeplearning/dataset/data

不加abspath
path=os.path.join(current,os.path.pardir,'dataset/data')
输出为/mnt/Data/aa/deeplearning/finalwork/../dataset/data

os.path.pardir为上一级,../
不加pardir
os.path.join(current,'dataset/data')
输出
/mnt/Data/aa/deeplearning/finalwork/dataset/data
加上以后
os.path.join(current,os.path.pardir,'dataset/data')
输出
/mnt/Data/aa/deeplearning/dataset/data

from imp import reload
reload(anno_func) 
# 上面两句话，可以重新加载代码
# 转换成one_hot编码
target_classes={'class':1,'class':2}
n_class=len(target_classes)
classes=np.array([int(target_classes[i]) for i in target_classes])
label = tf.cast(classes, tf.int32)
label = tf.one_hot(label,n_class,1,0)
sess=tf.Session()
print(sess.run(label))
sess.close()

from imp import reload
reload(anno_func)

上面两句话，可以重新加载代码

转换成one_hot编码

target_classes={‘class’:1,’class’:2}
n_class=len(target_classes)
classes=np.array([int(target_classes[i]) for i in target_classes])
label = tf.cast(classes, tf.int32)
label = tf.one_hot(label,n_class,1,0)
sess=tf.Session()
print(sess.run(label))
sess.close()