Caffe VS Caffe2

Compare Caffe vs Caffe2 and see what are their differences.

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Caffe Caffe2
6 -
33,859 8,443
0.2% -
0.0 0.0
2 months ago over 5 years ago
C++ Jupyter Notebook
GNU General Public License v3.0 or later -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Caffe

Posts with mentions or reviews of Caffe. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-16.

Caffe2

Posts with mentions or reviews of Caffe2. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Caffe2 yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing Caffe and Caffe2 you can also consider the following projects:

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

mlpack - mlpack: a fast, header-only C++ machine learning library

Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!

CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

Porcupine   - On-device wake word detection powered by deep learning

openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

CoreML-Models - Largest list of models for Core ML (for iOS 11+)

Theano - Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor