caffe

Why we included this project

Caffe was developed at Berkeley AI Research as a deep learning framework built around convolutional networks for vision work. Model definitions live in plain-text prototxt files, so you can describe an architecture and experiment with it without writing much code; the C++ core plus Python and MATLAB bindings covers both training and deployment. The project ships BAIR reference models and a community model zoo, which is handy when you want a starting point for image classification or feature extraction rather than building from scratch. It's also worth a look if you maintain older vision pipelines or want to understand where today's frameworks got their ideas, since Caffe's modular structure shows up in a lot of later tools.