PicPac: An Image Database and Streamer for Deep Learning

PicPac is an image database, explorer and streamer for deep learning. It is developed so that the user of different deep learning frameworks can all use the same image database format. PicPac currently supports streaming data into TensorFlow, MXNet, Torch and a Caffe fork, with C++, python and Lua API.

#Documentation

Prerequisits:

• boost libraries (libboost-all-dev on ubuntu or boost-devel on centos )
• opencv2 (libopencv-dev or opencv-devel)
• glog (libglog-dev or glog-devel)

pip install -i https://testpypi.python.org/pypi picpac

This will install the Python streaming API.

• Tensorflow Slim
• MXNet

• Public dataset imported to PicPac databases
• How to import data

PicPac Explorer is a Web-based UI that allows the user to explore the picpac database content and simulate streaming configurations.

Download portable distribution of PicPac Explorer here: (http://aaalgo.com/picpac/binary/).

Run picpac-explorer db and point the web browser to port 18888. If the program is executed under a GUI environment, the browser will be automatically opened.

The basic library depends on OpenCV 2.x and Boost. The dependency on Json11 is provided as git submodule, which can be pulled in by

git submodule init
git submodule update

PicPac Explorer for visualizing annotation results is built with separate rules and has many more dependencies. Use the link about to download a portable pre-built version.