研究背景
图像合成方向研究
学习参考
CVPR2016
CVPR2017
论文翻译学习
SSD中英对照
Yolo9000中英对照
Image Generation from Scene Graphs论文
Image Generation from Scene Graphs代码
环境配置
Ubuntu 16.04 LTS
- conda install pytorch
aria2c https://conda.anaconda.org/pytorch/linux-64/pytorch-0.4.1-py36_cuda9.0.176_cudnn7.1.2_1.tar.bz2
- conda install cuda
(ssdpytorch) ouc@ouc:~/data1/liuhongzhi$ conda install cudatoolkit==8.0
- conda install cudnn
(ssdpytorch) ouc@ouc:~/data1/liuhongzhi$ conda install cudnn
- install lua package
git clone https://github.com/qassemoquab/stnbhwd.git
cd stnbhwd
luarocks install *.rockspec
......
stnbhwd scm-1 is now built and installed in /home/ouc/data1/liuhongzhi/distro/install/ (license: MIT)
display scm-0 is now built and installed in /home/ouc/data1/liuhongzhi/distro/install/ (license: MIT)
使用luarocks list查看是否安装成功
(gawwn) ouc@ouc:~/data1/liuhongzhi/GAWWN$ luarocks list
Warning: Failed loading manifest for /home/ouc/.luarocks/lib/luarocks/rocks: /home/ouc/.luarocks/lib/luarocks/rocks/manifest: No such file or directory
Installed rocks:
----------------
argcheck
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
cudnn
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
cunn
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
cutorch
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
cwrap
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
dok
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
env
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
fn
0-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
gnuplot
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
graph
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
hdf5
20-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
image
1.1.alpha-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
logroll
0-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
lua-cjson
2.1devel-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
luaffi
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
luafilesystem
1.6.3-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
matio
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
moses
1.6.1-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
nn
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
nngraph
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
nnx
0.1-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
optim
1.0.5-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
paths
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
penlight
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
pprint
0-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
qtlua
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
qttorch
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
stnbhwd
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
sundown
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
sys
1.1-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
threads
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
torch
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
totem
0-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
trepl
scm-1 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
util
0-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
xlua
1.0-0 (installed) - /home/ouc/data1/liuhongzhi/distro/install/lib/luarocks/rocks
常用代码
1、生成AttnGAN需要的*.pickle文件
import pickle
#fi =open('huizong10000list.txt','w')
content = []
with open('vallist.txt', 'r') as f:
for line in f.readlines():
content.append(line.strip('\n'))
print(content)
#print(content,file=fi)
#fi.close()
output = open('vallist5000.pickle', 'wb')
pickle.dump(content, output, protocol=2)
output.close()
2、其他代码待整理
#导入模块
import pickle
fi =open("out.txt", "w")
#打开二进制文件
f = open('./coco/captions.pickle','rb')
n = pickle.load(f)
print("%3d %0.2f" % (year, principal), file = fi)
for i in range(n): #文件中有多少个对象就循环多个少次
x = pickle.load(f) #依次读取文件中对象
print(x)
#str = "a string to print to file"
#file =open('out.txt','w')
#print >>f,str
#file.close()
f.close()
import pickle
#fi =open('out.txt','w')
picklefile=open('./train/filenames.pickle','rb')
data=pickle.load(picklefile)
#print (data,file=fi)
print (data)
import pickle
#导入模块
import pickle
with open('huizong.txt','r',encoding='utf-8') as src,open('huizong.pickle','wb') as dest:
lines = src.readlines() #把源文件中的所有内容都读取到 lines 列表中
pickle.dump(len(lines),dest) #先写入对象个数
for line in lines:
pickle.dump(line,dest)
#上面就是已经把数据写入到二进制文件中了，下面从二进制文件中反序列化对象
with open('huizong.pickle','rb') as f:
n = pickle.load(f)
for i in range(n):
print(pickle.load(f))
import pickle
#fi =open('out.txt','w')
picklefile=open('huizong.pickle','rb')
data=pickle.load(picklefile)
#print (data,file=fi)
print (data)
import pickle
with open('huizong.txt', 'r') as fr:
data = fr.read()
print(data)
with open('huizong.pickle', 'wb') as fw:
pickle.dump(data, fw, pickle.HIGHEST_PROTOCOL)
with open('huizong.pickle', 'rb') as fr:
data = pickle.load(fr)
print(data)
file = open('huizong2.txt', 'w')
for i in range (len('huizong.txt')):
file.write(content[i]+'\n')
file.close()
f = open('huizong.pickle', 'wb')
test_content = text_read('huizong.txt')
def text_read(filename):
# Try to read a txt file and return a list.Return [] if there was a mistake.
try:
file = open(filename,'r')
except IOError:
error = []
return error
content = file.readlines()
for i in range(len(content)):
content[i] = content[i][:len(content[i])-1]
file.close()
return content
print(test_content,file=f)
import pickle
with open('huizong2.txt', 'r') as fr:
data = fr.read()
print(data)
with open('huizong.pickle', 'wb') as fw:
pickle.dump(data, fw, protocol=2)
with open('huizong.pickle', 'rb') as fr:
data = pickle.load(fr)
print(data)
import pickle
with open('huizong.pickle', 'rb') as fr:
data = pickle.load(fr)
print(data)
import pickle
with open('./train/filenames.pickle', 'rb') as fr:
data = pickle.load(fr)
print(data)
fi =open("out.txt", "w")
import pickle
with open('./train/filenames.pickle', 'rb') as fr:
data = pickle.load(fr)
print(data,file=fi)
import pickle
with open('huizong2.txt', 'r') as fr:
data = fr.read()
print(data)
with open('huizong.pickle', 'wb') as fw:
pickle.dump(data, fw, protocol=2)
with open('huizong.pickle', 'rb') as fr:
data = pickle.load(fr)
print(data)
import pickle
selfref_list = ['COCO_train2014_000000487025', 'COCO_train2014_000000526896']
selfref_list.append(selfref_list)
output = open('list2.pickle', 'wb')
pickle.dump(selfref_list, output, protocol=2)
output.close()
import pickle
selfref_list = ['COCO_train2014_000000000025','COCO_train2014_000000526896']
output = open('list2.pickle', 'wb')
pickle.dump(selfref_list, output, protocol=2)
output.close()
import sys
result=[]
with open('huizong10000.txt','r') as f:
for line in f:
result.append(list(line.strip('\n').split(',')))
print(result)
import sys
result1=[]
with open('huizong10000.txt','r') as f:
for line in f:
result1.append(line.strip('\n').split(','))
print(result1)
#coding=utf-8
content = []
with open('huizong10000.txt', 'r') as f:
for line in f.readlines():
content.append([line.strip('\n')])
print(content)
import pickle
fi =open('huizong10000list.txt','w')
content = []
with open('huizong10000.txt', 'r') as f:
for line in f.readlines():
content.append(line.strip('\n'))
print(content,file=fi)
fi.close()
output = open('list10000.pickle', 'wb')
pickle.dump(content, output, protocol=2)
output.close()
henry@henry-System-Product-Name:~/Files/AttnGAN/data/coco/newpickle$ ipython
Python 3.7.0 (default, Jun 28 2018, 13:15:42)
Type 'copyright', 'credits' or 'license' for more information
IPython 6.5.0 -- An enhanced Interactive Python. Type '?' for help.
In [1]: import pickle
...: fi =open('huizong10000list.txt','w')
...: content = []
...: with open('huizong10000.txt', 'r') as f:
...: for line in f.readlines():
...: content.append(line.strip('\n'))
...: print(content,file=fi)
...: fi.close()
...: output = open('list10000.pickle', 'wb')
...: pickle.dump(content, output, protocol=2)
...: output.close()
import pickle
selfref_list = ['COCO_train2014_000000151351', 'COCO_train2014_000000151352', 'COCO_train2014_000000151353', 'COCO_train2014_000000151364', 'COCO_train2014_000000151371', 'COCO_train2014_000000151375', 'COCO_train2014_000000151382', 'COCO_train2014_000000151405', 'COCO_train2014_000000151406', 'COCO_train2014_000000151408', 'COCO_train2014_000000151414', 'COCO_train2014_000000151455', 'COCO_train2014_000000151466', 'COCO_train2014_000000151483', 'COCO_train2014_000000151486', 'COCO_train2014_000000151497', 'COCO_train2014_000000151499', 'COCO_train2014_000000151523', 'COCO_train2014_000000151564', 'COCO_train2014_000000151566', 'COCO_train2014_000000151567', 'COCO_train2014_000000151573', 'COCO_train2014_000000151577', 'COCO_train2014_000000151587', 'COCO_train2014_000000151594', 'COCO_train2014_000000151599', 'COCO_train2014_000000151609', 'COCO_train2014_000000151611', 'COCO_train2014_000000151619', 'COCO_train2014_000000151637', 'COCO_train2014_000000151646', 'COCO_train2014_000000151655', 'COCO_train2014_000000151658', 'COCO_train2014_000000151678', 'COCO_train2014_000000151694', 'COCO_train2014_000000151702', 'COCO_train2014_000000151731', 'COCO_train2014_000000151756', 'COCO_train2014_000000151757', 'COCO_train2014_000000151761', 'COCO_train2014_000000151764', 'COCO_train2014_000000151787', 'COCO_train2014_000000151840', 'COCO_train2014_000000151848', 'COCO_train2014_000000151862', 'COCO_train2014_000000151869', 'COCO_train2014_000000151893', 'COCO_train2014_000000151900', 'COCO_train2014_000000151934', 'COCO_train2014_000000151959', 'COCO_train2014_000000151979', 'COCO_train2014_000000152003', 'COCO_train2014_000000152036', 'COCO_train2014_000000152038', 'COCO_train2014_000000152056', 'COCO_train2014_000000152060', 'COCO_train2014_000000152084', 'COCO_train2014_000000152099', 'COCO_train2014_000000152108', 'COCO_train2014_000000152162', 'COCO_train2014_000000152197', 'COCO_train2014_000000152209', 'COCO_train2014_000000152261', 'COCO_train2014_000000152265', 'COCO_train2014_000000152269', 'COCO_train2014_000000152273', 'COCO_train2014_000000152275', 'COCO_train2014_000000152294', 'COCO_train2014_000000152309', 'COCO_train2014_000000152354', 'COCO_train2014_000000152389', 'COCO_train2014_000000152397', 'COCO_train2014_000000152403', 'COCO_train2014_000000152405', 'COCO_train2014_000000152429', 'COCO_train2014_000000152431', 'COCO_train2014_000000152434', 'COCO_train2014_000000152461', 'COCO_train2014_000000152483', 'COCO_train2014_000000152488']
output = open('list10000.pickle', 'wb')
pickle.dump(selfref_list, output, protocol=2)
output.close()
3、Python 批量改变图像大小size代码
import os
from PIL import Image
import sys
#获取path目录下的所有文件
def get_imlist(path):
return[os.path.join(path,f) for f in os.listdir(path)]
def change_size(path):
directorys=get_imlist(path)
print("start directorys")
count = 0
for directory in directorys:
#不是图片文件就跳过
#if not(directory.endswith('j.jpg') or directory.endswith('b.bmp')):
# pass
#else:
count = count +1
print(count)
print("start!")
img=Image.open(directory)
s="/"
#获取文件名（含后缀）
oimage_name=directory[directory.rfind(s)+1:]
#获取原图的宽度和高度
(oimage_width,oimage_height)=img.size
if oimage_width==256 and oimage_height==256:
to_save=path+'/256_256/'+oimage_name
img.save(to_save)
#移除原图
os.remove(directory)
else:
to_save='/home/henry/Files/ICCV2019/cocostuffapi/PythonAPI/text2image/pix2pix/'+'/256/'+oimage_name # 保存路径
new_width=256
new_height=256
out=img.resize((new_width,new_height),Image.ANTIALIAS)
out.save(to_save)
os.remove(directory)
change_size("/home/henry/Files/ICCV2019/cocostuffapi/PythonAPI/text2image/pix2pix/trainresize") # 原始图像路径
4、根据txt中文件名，将指定文件复制到指定路径代码
import time
import os
import shutil
def re_mycopyfile(srcfile,dstfile,num):
#name_long=16
l=len(str(num))
zero='00000000'
newname = srcfile[-16:-4]
if not os.path.isfile(srcfile):
print "%s not exist!"%(srcfile)
else:
#fpath,fname=os.path.split(dstfile) #分离文件名和路径
if not os.path.exists(dstfile):
os.makedirs(dstfile) #创建路径
#dstfile=dstfile+zero[:name_long-l-1]+str(num)+'.txt'
dstfile = dstfile+str(newname)+'.txt'
print dstfile
shutil.copyfile(srcfile,dstfile) #复制文件
print "copy %s -> %s"%(srcfile,dstfile)
if __name__ == '__main__':
path1="/home/henry/Files/ICCV2019/cocostuffapi/PythonAPI/pic256.txt"
path2="/home/henry/Files/ICCV2019/cocostuffapi/PythonAPI/train2017all/"
path3="/home/henry/Files/ICCV2019/cocostuffapi/PythonAPI/train2017/"
path4="/home/henry/Files/ICCV2019/cocostuffapi/PythonAPI/trainnew.txt"
begin=0
count=begin
with open(path1,'r')as f:
for line in f:
line=line.split('\n')
print line[0]
srcfile = path2+str(line[0])
print srcfile
count=count+1
print count
dstfile=path3
re_mycopyfile(srcfile,dstfile,count)
count=begin
name_long=6
l=len(str(count+1))
zero='00000000'
with open(path1,'r')as f:
for line in f:
count=count+1
out_words=line.split('/')
#out_words[-1]=zero[:name_long-l-1]+str(count)+'.txt'
out_words[-1] = zero[:name_long - l - 1] + str(count) + '.txt'
with open(path4,'a+') as fp:
fp.write("/".join(out_words)+"\n")
5、ubuntu批量转换 png到jpg代码
----------- 从 PNG 转换到 JPG -----------
$ ls -1 *.png | xargs -n 1 bash -c 'convert "$0" "${0%.png}.jpg"'
----------- 从 JPG 转换到 PNG -----------
$ ls -1 *.jpg | xargs -n 1 bash -c 'convert "$0" "${0%.jpg}.png"'
-1 – 告诉 ls 每行列出一个图像名称的选项标识
-n – 指定最多参数个数，例子中为 1
-c – 指示 bash 运行给定的命令
${0%.png}.jpg – 设置新转换的图像文件的名字，% 符号用来删除源文件的扩展名
问题总结
- 1、ImportError: No module named torchvision
ImportError: No module named torchvision
- 2、ImportError: No module named yaml
解决办法
pip install pyyaml
3、Conda常用命令整理
Conda常用命令整理4 conda
ubuntu利用conda创建虚拟环境并安装cuda cudnn5 find 查找文件并复制到指定路径
src_dir 源目录
dst_dir 目标目录
access.log.2011102[2-6]* 文件名的正则表达式，获取文件的条件
方法1：
find src_dir -name "access.log.2011102[2-6]*" -exec cp {} dst_dir /
find src_dir -name "access.log.2011102[2-6]*" -exec scp {} 用户名@主机ip:dst_dir /
方法2：
find src_dir -name "access.log.2011102[2-6]*" |xargs -i cp {} dst_dir
find src_dir -name "access.log.2011102[2-6]*" |xargs -I {} cp {} dst_dir
find src_dir -name "access.log.2011102[2-6]*" |xargs -I {} scp {} 用户名@主机ip:dst_dir
方法3：
find ./ -path '/tmp/mnt/disk1/ignore' -prune -o /( -name '*' ! -name "*.tmp" /) | xargs cp "目的目录" "{}" /
- 6、OpenCV版本报错
ImportError: No module named 'cv2'
版本错误
AttributeError: 'module' object has no attribute 'CV_LOAD_IMAGE_COLOR'\
原因版本问题，opencv3使用
IMREAD_COLOR 代替'CV_LOAD_IMAGE_COLOR'
安装OpenCV
Run the following command:
conda install -c https://conda.binstar.org/menpo opencv
conda install -c https://conda.binstar.org/menpo opencv3
conda config --add channels menpo
conda install opencv (or opencv3)
conda install -c clinicalgraphics vtk
- CycleGAN
visdom
- 启动
python3 -m visdom.server
- 初始化
from visdom import Visdom
import numpy as np
viz = Visdom(env='loss')
x,y=0,0.2
win = viz.line( X=np.array([x]), Y=np.array([y]), opts=dict(title='loss'))
Visdom(server='http://localhost', endpoint='events', port=8097, ipv6=True, http_proxy_host=None, http_proxy_port=None, env='main', send=True, raise_exceptions=None, use_incoming_socket=True)
3.更新参数
viz.line(X=np.array([x_new]),Y=np.array([y_new]), win=win,update='append')
必备深度学习知识
- 给定一副测试图片输入(N,C,H,W)
参数 W 是图像的宽度，H 是高度，C 是通道的个数；彩色图像中 C = 3，灰度图像中C = 1
data_format 设置为[ N C H W ]时，排列顺序为 [batch, channels, height, width]，[批，通道数，高度，宽度]
