caffe.rs

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• =caffe.rs= [[https://travis-ci.org/ajtulloch/caffe.rs][https://travis-ci.org/ajtulloch/caffe.rs.svg?branch=master]]

A Rust FFI wrapper for the [[http://caffe.berkeleyvision.org/][Caffe]] deep learning library, using [[https://github.com/crabtw/rust-bindgen][rust-bindgen]].

** Setup Requires a =caffe= distribution built with the patches in =ajtulloch/caffe:caffe-ffi= (https://github.com/ajtulloch/caffe/tree/caffe-ffi) to expose the necessary structures over FFI.

You can clone and build that repository as usual. Set the =CAFFE_ROOT= environment variable to allow the =build.rs= script to correctly generate dependencies. ** Example *** Inference on a pre-trained network #+BEGIN_SRC rust // Create the newtork let mut net = caffe::Net::new(Path::new("test-data/lenet.prototxt"), caffe::Phase::Test); // Initialize the weights net.copy_trained_layers_from(Path::new("test-data/lenet.caffemodel"));

// Fill in the input data blob. let mut data_blob = net.blob("data"); let mut ones: Vec<_> = repeat(1.0 as f32) .take(data_blob.len()) .collect(); data_blob.set_data(ones.as_mut_slice());

// Run a foward pass. net.forward_prefilled(); let prob_blob = net.blob("prob");

// Process the output probabilities. let probs = prob_blob.as_slice(); println!("{:?}", probs.to_vec()); assert_eq!(probs[0], 0.06494621) #+END_SRC

*** Running a solver #+BEGIN_SRC rust let mut solver = caffe::Solver::new( Path::new("test-data/lenet_solver.prototxt")); solver.solve(); #+END_SRC