NAME¶

caffe - command line brew for Caffe

SYNOPSIS¶

 caffe <COMMAND> <FLAGS>

DESCRIPTION¶

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.

COMMANDS¶

train

train or finetune a model

test

score a model

device_query

show GPU diagnostic information

time

benchmark model execution time

FREQUENTLY USED FLAGS¶

-gpu

(Optional; run in GPU mode on given device IDs separated by ','. Use '-gpu all' to run on all available GPUs. The effective training batch size is multiplied by the number of devices.) type: string default: ""

-iterations

(The number of iterations to run.) type: int32 default: 50

-level

(Optional; network level.) type: int32 default: 0

-model

(The model definition protocol buffer text file..) type: string default: ""

-phase

(Optional; network phase (TRAIN or TEST). Only used for 'time'.) type: string default: ""

-sighup_effect

(Optional; action to take when a SIGHUP signal is received: snapshot, stop or none.) type: string default: "snapshot"

-sigint_effect

(Optional; action to take when a SIGINT signal is received: snapshot, stop or none.) type: string default: "stop"

-snapshot

(Optional; the snapshot solver state to resume training.) type: string default: ""

-solver

(The solver definition protocol buffer text file.) type: string default: ""

-stage

(Optional; network stages (not to be confused with phase), separated by ','.) type: string default: ""

-weights

(Optional; the pretrained weights to initialize finetuning, separated by ','. Cannot be set simultaneously with snapshot.) type: string default: ""

-help

Show complete help messages.

OTHER CAFFE UTILITIES¶

Apart from the "caffe" command line utility, there are also some utilities available, run them with "-h" or "--help" argument to see corresponding help.

• convert_imageset
• convert_cifar_data
• compute_image_mean
• convert_mnist_siamese_data
• upgrade_net_proto_binary
• extract_features
• upgrade_solver_proto_text
• classification
• upgrade_net_proto_text
• convert_mnist_data

EXAMPLES¶

Train a new Network

    $ caffe train -solver solver.prototxt

    $ caffe train -solver solver.prototxt -snapshot bvlc_alexnet.solverstate

    $ caffe train -solver solver.prototxt -weights pre_trained.caffemodel

    $ caffe test -model train_val.prototxt -weights bvlc_alexnet.caffemodel -gpu 0 -iterations 100

    $ caffe time -model deploy.prototxt -gpu 0

    $ caffe device_query -gpu 0

HOMEPAGE¶

http://caffe.berkeleyvision.org

BUGS¶

https://github.com/BVLC/caffe/issues

AUTHOR¶

This manpage is written by Zhou Mo <cdluminate@gmail.com> with the help of txt2man for Debian according to program's help message.