GraphPipe vs ML Kit: What are the differences?
Developers describe GraphPipe as "Machine Learning Model Deployment Made Simple, by Oracle". GraphPipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework-specific model implementations. On the other hand, ML Kit is detailed as "Machine learning for mobile developers (by Google)". ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
GraphPipe and ML Kit can be categorized as "Machine Learning" tools.
Some of the features offered by GraphPipe are:
- A minimalist machine learning transport specification based on flatbuffers
- Simple, efficient reference model servers for Tensorflow, Caffe2, and ONNX.
- Efficient client implementations in Go, Python, and Java.
On the other hand, ML Kit provides the following key features:
- Image labeling - Identify objects, locations, activities, animal species, products, and more
- Text recognition (OCR) - Recognize and extract text from images
- Face detection - Detect faces and facial landmarks
GraphPipe is an open source tool with 643 GitHub stars and 91 GitHub forks. Here's a link to GraphPipe's open source repository on GitHub.