TensorFlow Lite is a set of tools that help convert TensorFlow models to run on edge devices.
This is a collection of links to TFLite models along with sample apps, model zoo, helpful tools and learning resources. Please submit a PR if you would like to contribute your TFLite models, demo apps or know of any other TFLite learning resources.
Here are the TFLite models with app / device implementations, and references. Note: pretrained TFLite models from MediaPipe are included, which you can implement with or without MediaPipe.
Task | Model | App | Reference | Source |
---|---|---|---|
Classification | MobileNetV1 (download) | Android | iOS | Raspberry Pi | Overview | tensorflow.org |
Classification | MobileNetV2 | Skin Lesion Detection Android | Community |
Object detection | Quantized COCO SSD MobileNet v1 (download) | Android | iOS | Overview | tensorflow.org |
Object detection | YOLO | Flutter | Paper | Community |
Object detection | MobileNetV2 SSD (download) | Reference | MediaPipe |
License Plate detection | SSD MobileNet (download) | Flutter | Community |
Face detection | BlazeFace (download) | Paper | Model card | MediaPipe |
Hand detection & tracking | Download: Palm detection, 2D hand landmark, 3D hand landmark |
Blog post | Model card | MediaPipe |
Pose estimation | Posenet (download) | Android | Overview | tensorflow.org |
Segmentation | DeepLab V3 (download) | Flutter | Paper | Community |
Segmentation (Flutter Realtime) | DeepLab V3 (download) | Flutter | Paper | Community |
Segmentation | DeepLab V3 (download) | Android | iOS | Overview | tensorflow.org |
Hair Segmentation | Download | Paper | Model card | MediaPipe |
Style transfer | Download: Style prediction, Style transform |
Overview | tensorflow.org |
Task | Model | App | Reference | Source |
---|---|---|---|
Question & Answer | DistilBERT | Android | Hugging Face |
Text Generation | GPT-2 / DistilGPT2 | Android | Hugging Face |
Task | Model | App | Reference | Source |
---|---|---|---|
Speech Recognition | DeepSpeech | Reference | Mozilla |
TFLite models that could be implemented in apps and things:
- MobileNet- pretrained MobileNet v2 and v3 models.
- TFLite models
- from TensorFlow Lite website
- from TensorFlow Hub
Here is the list of TensorFlow models that could be converted to TFLite and then implemented in apps and things:
- Official TensorFlow models
- Tensorflow detection model zoo - pre-trained on COCO, KITTI, AVA v2.1, iNaturalist Species datasets)
- 2/9/219 Flutter + MLKit: Business Card Mail Extractor - tutorial | Flutter
- 2/8/2019 From TensorFlow to ML Kit: Power your Android application with machine learning - slides | Android (Kotlin)
- 8/7/2018 Building a Custom Machine Learning Model on Android with TensorFlow Lite - tutorial
- 7/27/2018 ML Kit on Android 4: Landmark Detection - tutorial
- 7/28/2018 ML Kit on Android 3: Barcode Scanning - tutorial
- 5/31/2018 ML Kit on Android 2: Face Detection - tutorial
- 5/22/2018 ML Kit on Android 1: Intro - tutorial
- Netron - for visualizing models.
- AI benchmark - for benchmarking computer vision models on smartphones.
Interested but not sure how to get started? Here are some learning resources that will help you whether you are a beginner or a practitioner in the field for a while.
- Official TensorFlow Lite documentation (link)
- 11/8/2019 - Getting Started with ML on MCUs with TensorFlow (link)
- 8/5/2019 - TensorFlow Model Optimization Toolkit — float16 quantization halves model size (link)
- 7/13/2018 - Training and serving a realtime mobile object detector in 30 minutes with Cloud TPUs (link)
- 6/11/2018 - Why the Future of Machine Learning is Tiny (link)
- 3/30/2018 - Using TensorFlow Lite on Android (link)
- 12/2019 - TinyML
- 10/2019 - Practical Deep Learning for Cloud, Mobile, and Edge
- 10/29/2019 - Inside TensorFlow: TensorFlow Lite
- 4/18/2018 - TensorFlow Lite for Android (Coding TensorFlow)
- Udacity Introduction to TensorFlow Lite
- Coursera Device-based Models with TensorFlow Lite