deepdetect

DeepDetect (http://www.deepdetect.com/) is a machine learning API and server written in C++11. It makes state of the art machine learning easy to work with and integrate into existing applications.

DeepDetect relies on external machine learning libraries through a very generic and flexible API. At the moment it has support for the deep learning library Caffe.

Main functionalities: DeepDetect implements support for supervised deep learning of images and other data, with focus on simplicity and ease of use, test and connection into existing applications.

Current features include:

• high-level API for machine learning
• JSON commnunication format
• dedicated server with support for asynchronous training calls
• high performances, benefit from multicores and GPU
• connector to handle large collections of images
• connector to handle CSV files with preprocessing capabilities
• range of built-in model assessment measures (e.g. F1, multiclass log loss, ...)
• no database dependency and sync, all information organized on the filesystem
• flexible template output format to simplify connection to external applications
• templates for the most useful neural architectures (e.g. Googlenet, Alexnet, mlp, logistic regression)

Documentation:

• Full documentation is available from http://www.deepdetect.com/overview/introduction/
• API documentation is available from http://www.deepdetect.com/api/

Dependencies:

• C++, gcc >= 4.8 or clang with support for C++11 (there are issues with Clang + Boost)
• eigen for all matrix operations;
• glog for logging events and debug;
• gflags for command line parsing;
• OpenCV >= 2.4
• cppnetlib
• Boost
• curl
• curlpp
• gtest for unit testing (optional);

Caffe Dependencies:

• CUDA 7 or 6.5 is required for GPU mode.
• BLAS via ATLAS, MKL, or OpenBLAS.
• protobuf
• IO libraries hdf5, leveldb, snappy, lmdb

Implementation: The code makes use of C++ policy design for modularity, performance and putting the maximum burden on the checks at compile time. The implementation uses many features from C++11.

Authors

DeepDetect is designed and implemented by Emmanuel Benazera [email protected].

Build

Below are instructions for Linux systems.

Beware of dependencies, typically on Debian/Ubuntu Linux, do:

sudo apt-get install build-essential libgoogle-glog-dev libgflags-dev libeigen3-dev libopencv-dev libcppnetlib-dev libboost-dev libcurlpp-dev libcurl4-openssl-dev protobuf-compiler libopenblas-dev libhdf5-dev libprotobuf-dev libleveldb-dev libsnappy-dev liblmdb-dev

For compiling along with Caffe:

mkdir build
cmake ..
make

Run tests

Note: running tests requires the automated download of ~75Mb of datasets, and computations may take around thirty minutes on a CPU-only machines.

To prepare for tests, compile with:

cmake -DBUILD_TESTS=ON ..
make

Start the server

cd build/main
./dede

DeepDetect [ commit 73d4e638498d51254862572fe577a21ab8de2ef1 ]
Running DeepDetect HTTP server on localhost:8080

Run examples

See tutorials from http://www.deepdetect.com/tutorials/tutorials/

References

• DeepDetect (http://www.deepdetect.com/)
• Caffe (https://github.com/BVLC/caffe)