CoreML-Models VS Caffe2

Compare CoreML-Models vs Caffe2 and see what are their differences.

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CoreML-Models Caffe2
2 0
6,180 8,443
- -
2.3 0.0
9 months ago over 5 years ago
Python Jupyter Notebook
MIT License -
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.

CoreML-Models

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

We haven't tracked posts mentioning CoreML-Models yet.
Tracking mentions began in Dec 2020.

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 CoreML-Models and Caffe2 you can also consider the following projects:

Caffe - Caffe: a fast open framework for deep learning.

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

Swift-AI - The Swift machine learning library.

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

Tensorflow-iOS

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

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

CoreML-samples - Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.

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

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

BrainCore - The iOS and OS X neural network framework