Awesome TensorFlow Lite

TensorFlow Lite is a set of tools that help convert and optimize TensorFlow models to run on mobile and edge devices. It's currently running on more than 4 billion devices! With TensorFlow 2.x, you can train a model with tf.Keras, easily convert a model to .tflite and deploy it; or you can download a pretrained TensorFlow Lite model from the model zoo.This is an awesome list of TensorFlow Lite models with sample apps, helpful tools and learning resources - * Showcase what the community has built with TensorFlow Lite * Put all the samples side-by-side for easy reference * Share knowledge and learning resourcesPlease submit a PR if you would like to contribute and follow the guidelines here.## Contents - Past announcements: - Models with samples - Computer vision - Classification - Detection - Segmentation - Style Transfer - Generative - Post estimation - Other - Text - Speech - Recommendation - Game - Model zoo - TensorFlow Lite models - TensorFlow models - Ideas and Inspiration - ML Kit examples - Plugins and SDKs - Helpful links - Learning resources - Blog posts - Books - Videos - Podcasts - MOOCsPast announcements:Here are some past feature annoucements of TensorFlow Lite: * Announcement of the new converter - MLIR-based and enables conversion of new classes of models such as Mask R-CNN and Mobile BERT etc., supports functional control flow and better error handling during conversion. Enabled by default in the nightly builds. * Android Support Library - Makes mobile development easier (Android sample code). * Model Maker - Create your custom image & text classification models easily in a few lines of code. See below the Icon Classifier for a tutorial by the community. * On-device training - It is finally here! Currently limited to transfer learning for image classification only but it's a great start. See the official Android sample code and another one from the community (Blog | Android). * Hexagon delegate - How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs. * Model Metadata - Provides a standard for model descriptions which also enables Code Gen and Android Studio ML Model Binding.Models with samplesHere are the TensorFlow Lite models with app / device implementations, and references. Note: pretrained TensorFlow Lite models from MediaPipe are included, which you can implement with or without MediaPipe.Computer visionClassification| Task | Model | App | Reference | Source |

awesome tflite

Awesome TensorFlow Lite

This is an awesome list of TensorFlow Lite models with sample apps, helpful tools and learning resources - * Showcase what the community has built with TensorFlow Lite * Put all the samples side-by-side for easy reference * Share knowledge and learning resources

Please submit a PR if you would like to contribute and follow the guidelines here.

## Contents - Past announcements: - Models with samples - Computer vision - Classification - Detection - Segmentation - Style Transfer - Generative - Post estimation - Other - Text - Speech - Recommendation - Game - Model zoo - TensorFlow Lite models - TensorFlow models - Ideas and Inspiration - ML Kit examples - Plugins and SDKs - Helpful links - Learning resources - Blog posts - Books - Videos - Podcasts - MOOCs

Past announcements:

Here are some past feature annoucements of TensorFlow Lite: * Announcement of the new converter - MLIR-based and enables conversion of new classes of models such as Mask R-CNN and Mobile BERT etc., supports functional control flow and better error handling during conversion. Enabled by default in the nightly builds. * Android Support Library - Makes mobile development easier (Android sample code). * Model Maker - Create your custom image & text classification models easily in a few lines of code. See below the Icon Classifier for a tutorial by the community. * On-device training - It is finally here! Currently limited to transfer learning for image classification only but it's a great start. See the official Android sample code and another one from the community (Blog | Android). * Hexagon delegate - How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs. * Model Metadata - Provides a standard for model descriptions which also enables Code Gen and Android Studio ML Model Binding.

Models with samples

Here are the TensorFlow Lite models with app / device implementations, and references. Note: pretrained TensorFlow Lite models from MediaPipe are included, which you can implement with or without MediaPipe.

Computer vision

Classification