Caffe Installation, Hello World
Note: tested with Ubuntu 16.04.1 using /root, for newer Ubuntu version (>= 17.04), check here.
Installation & Self-Tests #
Use the installation script here.
//(Sunny only added conditional USE_CUDNN=1, the rest is the same as: ref. You may wanna set USE_CUDNN to 0, if no GPU is used).
Timing: 15min if everything goes well, while downloading speed 1~8MB/s.
Hello World (Mnist) #
prepare data: #
./data/mnist/get_mnist.sh # will download into ./data/mnist/
./examples/mnist/create_mnist.sh # will create lmdb, compute image mean
train #
# < 1min on TitanX
./build/tools/caffe train -solver examples/mnist/lenet_solver.prototxt -gpu 0
updatedb && \
locate lenet_iter
//by default, -gpu device index is -1 (no gpu)
//The training can start from any training snapshot:
caffe train -solver=lenet_solver.prototxt -snapshot=lenet_iter_350.solverstate
(see the end of this article)
test #
cd
#git clone [email protected]:SunnyBingoMe/caffe-mnist-test.git
git clone https://github.com/SunnyBingoMe/caffe-mnist-test.git
cd caffe-mnist-test
python2 mnist_test.py 2.png
Build-in Default Examples #
CAFFE_ROOT=/root/caffe
echo 'CAFFE_ROOT=/root/caffe' >> ~/.bashrc
cd $CAFFE_ROOT
mnist #
Hand-writing digits.
prepare data: #
./data/mnist/get_mnist.sh # will download into ./data/mnist/
./examples/mnist/create_mnist.sh # will create lmdb, compute image mean
timing: #
# for cpu:
./build/tools/caffe time --model=examples/mnist/lenet_train_test.prototxt
# for gpu (just add the gpu param at the end):
./build/tools/caffe time --model=examples/mnist/lenet_train_test.prototxt --gpu 0
cifar10 #
ref: The CIFAR-10 dataset (<200MB) consists of 60000 32x32 colour images in 10 classes (animals), with 6000 images per class. There are 50000 training images and 10000 test images.
prepare data: #
./data/cifar10/get_cifar10.sh
./examples/cifar10/create_cifar10.sh
timing/benchmarking: #
# cpu:
./build/tools/caffe time --model=examples/cifar10/cifar10_full_train_test.prototxt
# gpu (just add the gpu param at the end):
./build/tools/caffe time --model=examples/cifar10/cifar10_full_train_test.prototxt --gpu 0
ilsvrc12 #
