如下代码会将npy的格式数据读出,并且输出来到控制台:
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import numpy as np ##设置全部数据,不输出省略号 import sys np.set_printoptions(threshold = sys.maxsize) boxes = np.load( './input_output/boxes.npy' ) print (boxes) print ( '---------------------boxes--------------------------' ) |
如下代码实现npy格式文件转换为txt,并且保存到当前目录相同文件名
实现转换整个文件夹下面多个文件:
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import os import numpy as np path = './input_output' #一个文件夹下多个npy文件, txtpath = './input_output' namelist = [x for x in os.listdir(path)] for i in range ( len (namelist) ): datapath = os.path.join(path,namelist[i]) #specific address print (namelist[i]) data = np.load(datapath).reshape([ - 1 , 2 ]) # (39, 2) np.savetxt( '%s/%s.txt' % (txtpath,namelist[i]),data) print ( 'over' ) import os import numpy as np path = './input_output' #一个文件夹下多个npy文件 txtpath = './input_output' namelist = [x for x in os.listdir(path)] for i in range ( len (namelist) ): datapath = os.path.join(path,namelist[i]) #specific address print (namelist[i]) #data = np.load(datapath).reshape([-1, 2]) # (39, 2) input_data = np.load(datapath) # (39, 2) data = input_data.reshape( 1 , - 1 ) np.savetxt( '%s/%s.txt' % (txtpath,namelist[i]),data) print ( 'over' ) |
同样的代码,实现读取单个npy文件,读取并且存储为txt :
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import numpy as np input_data = np.load(r "C:\test.npy" ) print (input_data.shape) data = input_data.reshape( 1 , - 1 ) print (data.shape) print (data) np.savetxt(r "C:\test.txt" ,data,delimiter = ',' ) |
修改pycharm的控制台的buffer大小:
如果你是用pycharm作为Python的编辑器,那么控制台的buf默认为1024,如果输出数据太多,需要修改buff大小才能让
全部数据输出,修改方法:
找到 pycharm 安装目录的 bin 目录下 idea.properties 文件, 修改 idea.cycle.buffer 值,原来默认为 1024
#--------------------------------------------------------------------- # This option controls console cyclic buffer: keeps the console output size not higher than the specified buffer size (Kb). # Older lines are deleted. In order to disable cycle buffer use idea.cycle.buffer.size=disabled #--------------------------------------------------------------------- idea.cycle.buffer.size=102400
补充知识:读取npy格式的文件
npy文件保存的是网络的权重
问题:Ubuntu环境下用gedit打开npy文件,是这样的,根本看不了内容
解决方法:编写如下代码,使解码后的文件内容输出在控制台
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import numpy as np context = np.load( 'E:/KittiSeg_pretrained0/vgg16.npy' ,encoding = "latin1" ) print (context) |
文件位置依据自己的存放位置进行修改
运行代码输出结果为
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{ 'conv1_2' : [array([[[[ 1.66219279e - 01 , 1.42701820e - 01 , - 4.02113283e - 03 , ..., 6.18828237e - 02 , - 1.74057148e - 02 , - 3.00644431e - 02 ], [ 9.46945231e - 03 , 3.87477316e - 03 , 5.08365929e - 02 , ..., - 2.77981739e - 02 , 1.71373668e - 03 , 6.82722731e - 03 ], [ 6.32681847e - 02 , 2.12877709e - 02 , - 1.63465310e - 02 , ..., 8.80054955e - 04 , 6.68104272e - 03 , - 1.41139806e - 03 ], ..., [ 3.47490981e - 03 , 8.47019628e - 02 , - 4.07223180e - 02 , ..., - 1.13523193e - 02 , - 7.48998486e - 03 , 3.19077494e - 03 ], [ 5.97234145e - 02 , 4.97663505e - 02 , - 3.23118735e - 03 , ..., 1.43114366e - 02 , 3.03175431e - 02 , - 4.23925705e - 02 ], [ 1.33459672e - 01 , 4.95484173e - 02 , - 1.78808011e - 02 , ..., 2.25385167e - 02 , 3.02020740e - 02 , - 2.17075031e - 02 ]], [[ 2.12007999e - 01 , 2.10127644e - 02 , - 1.47626130e - 02 , ..., 2.29580477e - 02 , 1.23102348e - 02 , - 3.08422819e - 02 ], [ - 2.62175221e - 03 , 7.42094172e - 03 , 6.74030930e - 02 , ..., - 3.06594316e - 02 , 1.80578313e - 03 , 4.27369215e - 03 ], [ 2.27197763e - 02 , - 1.07841045e - 02 , - 1.31095545e - 02 , ..., - 1.15751950e - 02 , 4.18359675e - 02 , - 1.92268589e - 03 ], ..., [ - 2.70304317e - 03 , 7.41161704e - 02 , - 3.32262330e - 02 , ..., - 1.10277236e - 02 , 1.39831286e - 02 , 5.34419343e - 03 ], [ - 3.20506282e - 02 , - 2.40584910e - 02 , - 4.52397857e - 03 , ..., - 6.04042644e - 03 , 2.01962605e - 01 , - 5.04491515e - 02 ], [ 1.68114193e - 02 , - 2.33167298e - 02 , - 1.40886130e - 02 , ..., - 7.79278344e - 03 , 1.28428593e - 01 , - 2.58184522e - 02 ]], [[ - 5.91698708e - 03 , - 2.26223674e - 02 , 4.88128467e - 03 , ..., 4.13784146e - 04 , - 4.84175496e - 02 , 1.63675251e - 03 ], [ - 3.93767562e - 03 , 9.07397643e - 03 , 5.36517277e - 02 , ..., - 2.56106984e - 02 , - 4.17886395e - 03 , 2.47476017e - 03 ], [ - 3.07008922e - 02 , - 1.09781921e - 02 , - 3.69096454e - 03 , ..., - 1.19221993e - 02 , - 1.39777903e - 02 , 8.52933805e - 03 ], ..., .......................................... |
以上这篇python实现npy格式文件转换为txt文件操作就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持服务器之家。
原文链接:https://blog.csdn.net/liqi849478873/article/details/92807316