diff options
| -rwxr-xr-x | examples/cifar10/create_cifar10.sh | 2 | ||||
| -rwxr-xr-x | examples/imagenet/create_imagenet.sh | 10 | ||||
| -rw-r--r-- | examples/mnist/convert_mnist_data.cpp | 7 | ||||
| -rwxr-xr-x | examples/mnist/create_mnist.sh | 2 | ||||
| -rw-r--r-- | examples/mnist/readme.md | 9 | ||||
| -rw-r--r-- | models/bvlc_alexnet/train_val.prototxt | 6 | ||||
| -rw-r--r-- | models/bvlc_reference_caffenet/train_val.prototxt | 6 |
7 files changed, 23 insertions, 19 deletions
diff --git a/examples/cifar10/create_cifar10.sh b/examples/cifar10/create_cifar10.sh index ad5038e0..dfba7cca 100755 --- a/examples/cifar10/create_cifar10.sh +++ b/examples/cifar10/create_cifar10.sh @@ -13,6 +13,6 @@ rm -rf $EXAMPLE/cifar10_train_leveldb $EXAMPLE/cifar10_test_leveldb echo "Computing image mean..." ./build/tools/compute_image_mean $EXAMPLE/cifar10_train_leveldb \ - $EXAMPLE/mean.binaryproto + $EXAMPLE/mean.binaryproto leveldb echo "Done." diff --git a/examples/imagenet/create_imagenet.sh b/examples/imagenet/create_imagenet.sh index a286b8fe..e912ac43 100755 --- a/examples/imagenet/create_imagenet.sh +++ b/examples/imagenet/create_imagenet.sh @@ -1,5 +1,5 @@ #!/usr/bin/env sh -# Create the imagenet leveldb inputs +# Create the imagenet lmdb inputs # N.B. set the path to the imagenet train + val data dirs EXAMPLE=examples/imagenet @@ -34,7 +34,7 @@ if [ ! -d "$VAL_DATA_ROOT" ]; then exit 1 fi -echo "Creating train leveldb..." +echo "Creating train lmdb..." GLOG_logtostderr=1 $TOOLS/convert_imageset \ --resize_height=$RESIZE_HEIGHT \ @@ -42,9 +42,9 @@ GLOG_logtostderr=1 $TOOLS/convert_imageset \ --shuffle \ $TRAIN_DATA_ROOT \ $DATA/train.txt \ - $EXAMPLE/ilsvrc12_train_leveldb + $EXAMPLE/ilsvrc12_train_lmdb -echo "Creating val leveldb..." +echo "Creating val lmdb..." GLOG_logtostderr=1 $TOOLS/convert_imageset \ --resize_height=$RESIZE_HEIGHT \ @@ -52,6 +52,6 @@ GLOG_logtostderr=1 $TOOLS/convert_imageset \ --shuffle \ $VAL_DATA_ROOT \ $DATA/val.txt \ - $EXAMPLE/ilsvrc12_val_leveldb + $EXAMPLE/ilsvrc12_val_lmdb echo "Done." diff --git a/examples/mnist/convert_mnist_data.cpp b/examples/mnist/convert_mnist_data.cpp index 19040153..2749e452 100644 --- a/examples/mnist/convert_mnist_data.cpp +++ b/examples/mnist/convert_mnist_data.cpp @@ -1,6 +1,5 @@ -// -// This script converts the MNIST dataset to the leveldb format used -// by caffe to perform classification. +// This script converts the MNIST dataset to a lmdb (default) or +// leveldb (--backend=leveldb) format used by caffe to load data. // Usage: // convert_mnist_data [FLAGS] input_image_file input_label_file // output_db_file @@ -176,7 +175,7 @@ int main(int argc, char** argv) { #endif gflags::SetUsageMessage("This script converts the MNIST dataset to\n" - "the leveldb/lmdb format used by Caffe to perform classification.\n" + "the lmdb/leveldb format used by Caffe to load data.\n" "Usage:\n" " convert_mnist_data [FLAGS] input_image_file input_label_file " "output_db_file\n" diff --git a/examples/mnist/create_mnist.sh b/examples/mnist/create_mnist.sh index 8c43dc33..06ecc27d 100755 --- a/examples/mnist/create_mnist.sh +++ b/examples/mnist/create_mnist.sh @@ -1,5 +1,5 @@ #!/usr/bin/env sh -# This script converts the mnist data into leveldb/lmdb format, +# This script converts the mnist data into lmdb/leveldb format, # depending on the value assigned to $BACKEND. EXAMPLE=examples/mnist diff --git a/examples/mnist/readme.md b/examples/mnist/readme.md index ac1a0b7d..44e0091f 100644 --- a/examples/mnist/readme.md +++ b/examples/mnist/readme.md @@ -19,7 +19,7 @@ You will first need to download and convert the data format from the MNIST websi cd $CAFFE_ROOT/examples/mnist ./create_mnist.sh -If it complains that `wget` or `gunzip` are not installed, you need to install them respectively. After running the script there should be two datasets, `mnist-train-leveldb`, and `mnist-test-leveldb`. +If it complains that `wget` or `gunzip` are not installed, you need to install them respectively. After running the script there should be two datasets, `mnist_train_lmdb`, and `mnist_test_lmdb`. ## LeNet: the MNIST Classification Model @@ -37,13 +37,14 @@ Specifically, we will write a `caffe::NetParameter` (or in python, `caffe.proto. ### Writing the Data Layer -Currently, we will read the MNIST data from the leveldb we created earlier in the demo. This is defined by a data layer: +Currently, we will read the MNIST data from the lmdb we created earlier in the demo. This is defined by a data layer: layers { name: "mnist" type: DATA data_param { - source: "mnist-train-leveldb" + source: "mnist_train_lmdb" + backend: LMDB batch_size: 64 scale: 0.00390625 } @@ -51,7 +52,7 @@ Currently, we will read the MNIST data from the leveldb we created earlier in th top: "label" } -Specifically, this layer has name `mnist`, type `data`, and it reads the data from the given leveldb source. We will use a batch size of 64, and scale the incoming pixels so that they are in the range \[0,1\). Why 0.00390625? It is 1 divided by 256. And finally, this layer produces two blobs, one is the `data` blob, and one is the `label` blob. +Specifically, this layer has name `mnist`, type `data`, and it reads the data from the given lmdb source. We will use a batch size of 64, and scale the incoming pixels so that they are in the range \[0,1\). Why 0.00390625? It is 1 divided by 256. And finally, this layer produces two blobs, one is the `data` blob, and one is the `label` blob. ### Writing the Convolution Layer diff --git a/models/bvlc_alexnet/train_val.prototxt b/models/bvlc_alexnet/train_val.prototxt index 69b8916d..717b6fa4 100644 --- a/models/bvlc_alexnet/train_val.prototxt +++ b/models/bvlc_alexnet/train_val.prototxt @@ -5,7 +5,8 @@ layers { top: "data" top: "label" data_param { - source: "examples/imagenet/ilsvrc12_train_leveldb" + source: "examples/imagenet/ilsvrc12_train_lmdb" + backend: LMDB batch_size: 256 } transform_param { @@ -21,7 +22,8 @@ layers { top: "data" top: "label" data_param { - source: "examples/imagenet/ilsvrc12_val_leveldb" + source: "examples/imagenet/ilsvrc12_val_lmdb" + backend: LMDB batch_size: 50 } transform_param { diff --git a/models/bvlc_reference_caffenet/train_val.prototxt b/models/bvlc_reference_caffenet/train_val.prototxt index d6d64073..073d8aef 100644 --- a/models/bvlc_reference_caffenet/train_val.prototxt +++ b/models/bvlc_reference_caffenet/train_val.prototxt @@ -5,7 +5,8 @@ layers { top: "data" top: "label" data_param { - source: "examples/imagenet/ilsvrc12_train_leveldb" + source: "examples/imagenet/ilsvrc12_train_lmdb" + backend: LMDB batch_size: 256 } transform_param { @@ -21,7 +22,8 @@ layers { top: "data" top: "label" data_param { - source: "examples/imagenet/ilsvrc12_val_leveldb" + source: "examples/imagenet/ilsvrc12_val_lmdb" + backend: LMDB batch_size: 50 } transform_param { |