Caffe 使用1：准备数据 Caffe DIY-step1: Prepare Data

Before using Caffe, we need to prepare data (mainly pictures)to feed the model.

Execute environment:

All the scripts has been put in the folder ~/caffe/caffe/data/myself

The current path is : ~/caffe/caffe/data/myself$

1. Resize(This has been integrated into the step3 in our new version).

We first resize our pictures to 256x256 by using

resizeImage.sh

for name in /path/to/imagenet/val/*.JPEG; do
convert -resize 256x256\! $name $name
done

2. Convert to lmdbFirstly, We can use the script as follows to create the file list.

File Name: creatFilelist.sh

Code:

#!/usr/bin/env sh
# creat the file list

DATA=.

echo "Create train.txt..."

rm -i $DATA/train.txt
find $DATA/cats/ -name '*.jpg' | cut -d '/' -f3 | sed "s/$/ 1/">>$DATA/train.txt
find $DATA/birds/ -name '*.jpg' | cut -d '/' -f3 | sed "s/$/ 2/">>$DATA/tmp.txt
cat $DATA/tmp.txt>>$DATA/train.txt
rm -i $DATA/tmp.txt

echo "Done.."

whereas the folder containing pictures are in current path, the folder 'cats' contains pictures of cats and the folder 'birds' contains pictures of birds.

Secondly, we can use the following script to convert the images to lmdb

File Name: convertImages.sh

Code:

#!/usr/bin/env sh
# conver pictures to the lmdb file

DATA=.

rm -ri $DATA/img_train_lmdb
../../build/tools/convert_imageset --shuffle \
--resize_height=256 --resize_width=256 \
/home/liu/caffe/caffe/data/myself/ $DATA/train.txt  $DATA/img_train_lmdb

3. Calculate the mean value

By calculating the mean value we can get higher speed and accuracy

File Name:make_myself_mean

Code:

#!/usr/bin/env sh
# Compute the mean image from the imagenet training lmdb
# N.B. this is available in data/ilsvrc12

EXAMPLE=.
DATA=.
TOOLS=../../build/tools

$TOOLS/compute_image_mean $EXAMPLE/img_train_lmdb \
  $DATA/img_mean.binaryproto

echo "Done."

reference:

1. Caffe学习系列(12)：训练和测试自己的图片 - denny402 - 博客园  http://www.cnblogs.com/denny402/p/5083300.html