Training artificial intelligence (AI) to recognize images is analogous to teaching a child, perhaps with some coding. After the success of TensorFlow as a robust machine learning framework, TensorFlow Lite is reinforcing machine learning on mobile devices. As a well-experienced provider of tensorflow development services, Oodles AI presents a comprehensive guide to deploy image classification with TensorFlow Lite.
What is TensorFlow Lite?
TensorFlow Lite (.TFLITE) is a lighter version of Google’s open-source machine learning framework, TensorFlow. The lightweight solution, TensorFlow Lite, is uniquely designed to run machine learning models on mobile and embedded devices.
Built to support the memory and compute constraints of quantized devices, TensorFlow Lite is emerging as a great initiative for running serverless ML applications.
However, .TFLITE can only deploy pre-existing models and a suite of tools to prepare models for mobile and embedded devices. For training models from scratch, one needs to incur a round trip to TensorFlow and convert the model to .TFLITE format. The converted model can then be pushed into a mobile interpreter with support via Java and C++ API, as demonstrated in the architecture below-
How Image Classification with TensorFlow Lite Works
Image classification using machine learning frameworks automates the identification of people, animals, places, and activities in an image. With domain-specific training, image classification models can predict what an image represents from fruits to food and more.
Step 1: Picking a model
One can either train a model using TensorFlow and convert it into .TFLITE format or use a pre-trained model provided by Google. ML models, including image classification, object detection, smart reply, etc. can be re-trained to process new categories of inputs. The method of re-training is often called “transfer learning” that is considerably more convenient than training from scratch.
Using TensorFlow Lite to Build Image Classification Models with Oodles
We, at Oodles, are well-positioned providers of artificial intelligence services for enterprises and organizations. We have hands-on experience in deploying third-party machine learning frameworks such as TensorFlow and TensorFlow Lite for-
a) Image Recognition
Have a deep look: Image Classification with TensorFlow Lite on Android