An object oriented (OOP) approach to train Tensorflow models and serve them using Tensorflow Serving.
-
Updated
Mar 7, 2022 - Python
An object oriented (OOP) approach to train Tensorflow models and serve them using Tensorflow Serving.
Custom Mask R-CNN matterport's model with tensorflow serving
Visual insights which is a web application built using the library dash plotly and FLask functionalities
Provide your prediction model through the Tensorflow Serving REST API
Add a description, image, and links to the tensorflow-serving-rest-api topic page so that developers can more easily learn about it.
To associate your repository with the tensorflow-serving-rest-api topic, visit your repo's landing page and select "manage topics."