awesome-tensorflow-lite
by margaretmz
An awesome list of TensorFlow Lite models, samples, tutorials, tools and learning resources.
AI summary
ML frameworks
A curated collection of TensorFlow Lite models and resources for developers to build and deploy machine learning applications on mobile devices.
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What's in the list
137 links in 18 sections, with live GitHub stats.activeno commit in 2y
Past announcements:
- Announcement of the new converter
-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 ( sample code)
- Model Maker
Create your custom 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 sample code and another one from the community ( | )
How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post
- Model Metadata
Provides a standard for model descriptions which also enables
Models with samples / Computer vision
- download
MobileNetV1 ( )
| | |
- Codelab
Recognize Flowers on Android |
Android
Skin Lesion Detection
- Colab Notebook
American Sign Language Detection | |
- Colab Notebook
Stone Paper Scissor Detection |
EfficientNet-Lite0 ( )
Icon Classifier | |
- download
Quantized COCO SSD MobileNet v1 ( )
| |
download
MobileNetV2 SSD ( )
- Paper
MobileDet ( )
(download)
SSD MobileNet
BlazeFace ( )
Palm detection & hand landmarks ( )
- Blog post
| |
- download
DeepLab V3 ( )
| | Flutter | |
Different variants of
- TF Hub
Models on with Colab Notebooks
- Overview
| |
- TF Hub
Models on with Colab Notebooks
- Dynamic range models
Download: )
DeepLabV3 & Style Transfer
| |
U-GAT-IT
(Selfie2Anime)
| |
| |
- TF Hub
Boundless on
- download
Posenet ( )
| |
download
MoveNet Lightning ( )
Project repo
| |
Yolov5 Inference
Flutter
Android
Arbitrary image stylization
White-box CartoonGAN
Project RepositoryModels with samples / Text
AndroidModels with samples / Speech
Reference
AndroidModels with samples / Recommendation
| |
Models with samples / Game
FlutterModel zoo / TensorFlow Lite models
Pretrained MobileNet v2 and v3 models
Model zoo / TensorFlow Lite models / TensorFlow Lite models
- TensorFlow Lite models
With official Android and iOS examples
- Pretrained models
Quantized and floating point variants
- TensorFlow Hub
Set "Model format = TFLite" to find TensorFlow Lite models
Model zoo / TensorFlow models
Official TensorFlow models
Pre-trained on COCO, KITTI, AVA v2.1, iNaturalist Species datasets
Ideas and Inspiration
E2E TFLite Tutorials
Checkout this repo for sample app ideas and seeking help for your tutorial projects. Once a project gets completed, the links of the TensorFlow Lite model(s), sample code and tutorial will be added to this awesome list
ML Kit examples
- ML Kit Translate demo
2019-10-01 - A tutorial with material design (Kotlin) sample - recognize, identify Language and translate text from live camera with ML Kit for Firebase
- Flutter + MLKit: Business Card Mail Extractor
2019-02-09 - A blog post with a sample code
- From TensorFlow to ML Kit: Power your Android application with machine learning
2019-02-08 - A talk with (Kotlin) sample code
- ML Kit and Face Detection in Flutter
2018-07-20
- ML Kit on Android 4: Landmark Detection
2018-07-27
- ML Kit on Android 3: Barcode Scanning
2018-07-28
- ML Kit on Android 2: Face Detection
2018-05-31
- ML Kit on Android 1: Intro
2018-05-22
Plugins and SDKs
- Edge Impulse
Created by to help you to train TensorFlow Lite models for embedded devices in the cloud
A cross platform (mobile, desktop and Edge TPUs) AI pipeline by Google AI. (PM ) |
- Coral Edge TPU
Edge hardware by Google.
TensorFlow Lite Flutter Plugin
Provides a dart API similar to the TensorFlow Lite Java API for accessing TensorFlow Lite interpreter and performing inference in flutter apps.
Helpful links
Netron
A tool for visualizing models
- AI benchmark
A website for benchmarking computer vision models on smartphones
- Performance measurement
How to measure model performance on Android and iOS
- Material design guidelines for ML
How to design machine learning powered features. A good example:
- The People + AI Guide book
Learn how to design human-centered AI products
A repository showing non-trivial conversion processes and general explorations in TensorFlow Lite
TFProfiler
An Android-based app to profile TensorFlow Lite models and measure its performance on smartphone
TensorFlow Lite Examples - Android
A repository refactors and rewrites all the TensorFlow Lite Android examples which are included in the TensorFlow official website
Tensorflow-lite-kotlin-samples
A collection of Tensorflow Lite Android example Apps in Kotlin, to show different kinds of kotlin implementation of the
Learning resources / Blog posts
- On-device training in TensorFlow Lite
2021-11-09
- YOLOv3 to TensorFlow Lite Conversion
2020-12-29 - By Nitin Tiwari
- What is new in TensorFlow Lite
2020-04-20 - By Khanh LeViet
- Optimizing style transfer to run on mobile with TFLite
2020-04-17 - By Khanh LeViet and Luiz Gustavo Martins
- How TensorFlow Lite helps you from prototype to product
2020-04-14 - By Khanh LeViet
- Getting Started with ML on MCUs with TensorFlow
2019-11-08 - By Brandon Satrom
- TensorFlow Model Optimization Toolkit — float16 quantization halves model size
2019-08-05 - By the TensorFlow team
- Training and serving a real-time mobile object detector in 30 minutes with Cloud TPUs
2018-07-13 - By Sara Robinson, Aakanksha Chowdhery, and Jonathan Huang
- Why the Future of Machine Learning is Tiny
2018-06-11 - - By Pete Warden
- Using TensorFlow Lite on Android
2018-03-30 - ) - By Laurence Moroney
Learning resources / Books
- AI and Machine Learning On-Device Development
2021-12-01 (early access) - By Laurence Moroney ( )
- AI and Machine Learning for Coders
2020-10-01 - By Laurence Moroney ( )
- Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter
2020-04-06 : Build scalable real-world projects to implement end-to-end neural networks on Android and iOS ( ) - By Anubhav Singh ( ) and Rimjhim Bhadani ( )
- Complete Bundle
2020-03-01 Raspberry Pi for Computer Vision ( | ) - By the PyImageSearch Team: Adrian Rosebrock ( ), David Hoffman, Asbhishek Thanki, Sayak Paul ( ), and David Mcduffee
- TinyML
2019-12-01 - By Pete Warden ( ) and Daniel Situnayake ( )
- Practical Deep Learning for Cloud, Mobile, and Edge
2019-10-01 - By Anirudh Koul ( ), Siddha Ganju ( ), and Meher Kasam ( )
Learning resources / Videos
- Contributing to TensorFlow Lite with Sunit Roy
2021-10-06 (Hacktoberfest 2021)
- Android ML by Hoi Lam
2020-07-25 (GDG Kolkata meetup)
- Easy on-device ML from prototype to production
2020-04-01 (TF Dev Summit 2020)
- TensorFlow Lite: ML for mobile and IoT devices
2020-03-11 (TF Dev Summit 2020)
- Inside TensorFlow: TensorFlow Lite
2019-10-29
Learning resources / Podcasts
- Talking Machine Learning with Hoi Lam
2020-08-08
Learning resources / MOOCs
- Introduction to TensorFlow Lite
Udacity course by Daniel Situnayake (@dansitu), Paige Bailey ( ), and Juan Delgado
- Device-based Models with TensorFlow Lite
Coursera course by Laurence Moroney ( )
- The Future of ML is Tiny and Bright
A series of edX courses created by Harvard in collaboration with Google. Instructors - Vijay Janapa Reddi, Laurence Moroney, and Pete Warden
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