caffe制作数据集

caffe根目录下新建myself文件夹，作为存放地址。新建test.py，生成train.txt和val.txt，作为数据集图片的说明。以下为test.py，和train文件夹、val

caffe根目录下新建myself文件夹，作为存放地址。 新建test.py，生成train.txt和val.txt，作为数据集图片的说明。 以下为test.py，和train文件夹、val文件夹放在同一路径下。train文件夹中有Neg_train文件夹和Pos_train文件夹。分别存放正负样本。val文件夹中有Neg_val文件夹和Pos_val文件夹。(使用时注意修改py文件中的路径)

''''' Created on Jul 29, 2016 @author: sgg ''' ""font-family:Arial;font-size:18px;"">" ""font-size:18px;"">" ""font-size:18px;"">" import os def IsSubString(SubStrList,Str): flag=True for substr in SubStrList: if not(substr in Str): flag=False return flag def GetFileList(FindPath,FlagStr=[]): FileList=[] FileNames=os.listdir(FindPath) if len(FileNames)>0: for fn in FileNames: if len(FlagStr)>0: if IsSubString(FlagStr,fn): fullfilename=os.path.join(FindPath,fn) FileList.append(fullfilename) else: fullfilename=os.path.join(FindPath,fn) FileList.append(fullfilename) if len(FileList)>0: FileList.sort() return FileList train_txt=open('train.txt','w') imgfile=GetFileList('train/Pos_train')for img in imgfile: str1=img+' '+'1'+'\n' train_txt.writelines(str1) imgfile=GetFileList('train/Neg_train') for img in imgfile: str2=img+' '+'0'+'\n' train_txt.writelines(str2) train_txt.close() test_txt=open('val.txt','w') imgfile=GetFileList('val/Pos_val')for img in imgfile: str3=img+' '+'1'+'\n' test_txt.writelines(str3) imgfile=GetFileList('val/Neg_val') for img in imgfile: str4=img+' '+'0'+'\n' test_txt.writelines(str4) test_txt.close() print("success")

准备生成lmbd文件。在myself文件夹下新建文件夹Build_lmbd. 从/home/seu/caffe/examples/imagenet路径下 拷贝create_imagenet.sh，修改使用。拷贝到Build_lmbd中。 修改路径后如下：

#!/usr/bin/env sh# Create the imagenet lmdb inputs# N.B. set the path to the imagenet train + val data dirsset -eEXAMPLE=myself/Build_lmbdDATA=myself/SampleTOOLS=build/toolsTRAIN_DATA_ROOT=/home/seu/caffe/myself/VAL_DATA_ROOT=/home/seu/caffe/myself/# Set RESIZE=true to resize the images to 256x256. Leave as false if images have# already been resized using another tool.RESIZE=falseif $RESIZE; then RESIZE_hljs-number">256 RESIZE_hljs-number">256else RESIZE_hljs-number">0 RESIZE_hljs-number">0fiif [ ! -d "$TRAIN_DATA_ROOT" ]; then echo "Error: TRAIN_DATA_ROOT is not a path to a directory: $TRAIN_DATA_ROOT" echo "Set the TRAIN_DATA_ROOT variable in create_imagenet.sh to the path" \ "where the ImageNet training data is stored." exit 1fiif [ ! -d "$VAL_DATA_ROOT" ]; then echo "Error: VAL_DATA_ROOT is not a path to a directory: $VAL_DATA_ROOT" echo "Set the VAL_DATA_ROOT variable in create_imagenet.sh to the path" \ "where the ImageNet validation data is stored." exit 1fiecho "Creating train lmdb..."GLOG_logtostderr=1 $TOOLS/convert_imageset \ --resize_hljs-variable">$RESIZE_HEIGHT \ --resize_hljs-variable">$RESIZE_WIDTH \ --shuffle \ $TRAIN_DATA_ROOT \ $DATA/train.txt \ $EXAMPLE/ilsvrc12_train_lmdbecho "Creating val lmdb..."GLOG_logtostderr=1 $TOOLS/convert_imageset \ --resize_hljs-variable">$RESIZE_HEIGHT \ --resize_hljs-variable">$RESIZE_WIDTH \ --shuffle \ $VAL_DATA_ROOT \ $DATA/val.txt \ $EXAMPLE/ilsvrc12_val_lmdbecho "Done."

在caffe根目录下运行后。 seu@my-pc:~/caffe$ sudo ./myself/Build_lmbd/create_imagenet.sh 可以看到生成结果：

参考博客：http://blog.csdn.net/liuweizj12/article/details/52149743