如下代码会将npy的格式数据读出，并且输出来到控制台： 复制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) np.savetxt(./input_output/boxes.txt,boxes,fmt=%s,newline=\\\\n)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： 复制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 addressprint(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 addressprint(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 : 复制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 复制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 复制{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],...,.......................................... 相关学习推荐：python视频教程